WO2011124220A1 - Newreporter system, arrangements and methods for video platforms - Google Patents

Abstract

The invention relates to a so-called Newreporter system (100) and/or arrangements, and/or methods for classifying image data and/or image data streams, especially real-time distributed image data that are distributed via at least one computer network (140). The Newreporter system (100) or an arrangement comprise the following elements: a. at least one classification unit (130) which is designed to classify image data and/or image data streams, at least one classification (132) being carried out due to or taking into consideration at least one client information (120); b. at least one client information (120) being associated with at least one client (110) that interacts with a Newreporter system (100) via at least one computer network, and said client (110) being able to transmit or/and receive image data.

Description

 SYSTEM AND METHOD FOR DETERMINING THE RELEVANCE OF VIDEOS FOR USERS

1. Technical area

 The invention relates to methods, arrangements and a system for a video platform. The invention, hereafter referred to as Newreporter System, has been made with particular attention to the possible application with wireless clients in one or more computer networks, in particular their communication with or via the Internet.

 2. State of the art

 10 Nowadays, the Internet is increasingly becoming the communication hub for humans. The trend is that more and more network traffic is coming from mobile phones or other mobile clients. Users are increasingly starting to load or retrieve content from their mobile phone to the Internet. A big problem here is the size of the display of mobile phones. It is difficult to present information to the user in the same way

15 at a glance for him interesting content can overlook. Therefore, the challenge arises that the user gets presented only information that seems interesting to him.

 For a client with a larger screen, the problem of presentation does not seem so acute because more information can be displayed. But due to the limited perceptibility and variety of content, it would also be an advantage if only information is displayed that is also of interest to the user.

 With stored information, the user can use search engines to display them, but with information transmitted in real time or near real time, this capability is often unavailable.

 25 A big trend is that user-generated videos are not available on platforms like B. YouTube. Due to the development of data speeds of mobile Internet access, it is technically possible not only to upload videos but also to stream live streams to the Internet.

 Therefore, the next stage of development of the Internet is likely to involve a massive amount of 30 user-generated video streams sent and viewed near real-time.

 This will pose new challenges to the presentation and selection of these video streams.

DE102005032681A1 describes a method and system for carrying out an interactive television session. However, no reference is made to the information overload and user-generated content. DE102008002276A1 describes a method and an arrangement for embedding mobile picture material in television programs. The disadvantage here is that the method is not aimed at viewers for whom various content is relevant.

 US20080216131 describes a method and system for sharing video over a computer network. Here, as before, the problem is that there is no possibility of relevance assessment for users.

 Qik (http://qik.com/) is a community that allows you to stream videos from mobile phones or English. Streaming (transfer of a data stream) called and to transmit to different customers. One limitation is that it is not possible to display videos that are relevant to a user sorted by relevance. Furthermore, users can not distribute tags in videos.

 Stickam (http://www.stickam.com) is a video chat and live streaming platform. Streams and related users on multiple pages can be sorted by the StreamRank ™ algorithm. This is mainly based on the fact that the ranking of a user increases, the more active and well-known he is. The limitation here is that the viewer's user data is not included. With this restriction, the other functions, such as rankings for the most viewed or "co-ordered" streams of users, are also limited.The search function can also search for terms, but the sorting of the result is not directed to the relevance for the user, but only after whose search words.

 Stickam or Qik are similar to Livecliq (http://www.livecliq.net/). Flixwagon

(Http://www.flixwagon.com/). Livecast (http://www.livecast.com/) and Bambuser

(Http://bambuser.com/). Another video platform is Seero (http://www.seero.com). This allows Live GPS to track data changes in videos and display them in a map.

 Due to further limitations of the portals that currently exist, there is additional room for improvement of features that can add value to users.

The present invention is therefore based on the technical problem of providing a system, an arrangement and a method which makes it possible to determine the relevance of videos or video streams for users. Furthermore, such a system and method should thereby also support a wide variety of clients and be usable in a computer network while still using other platforms such as e.g. Social networks work together. In addition, such a system should provide capabilities to enable a next-generation video platform.

3. Brief description of the invention:

The problems of the prior art are solved according to a first aspect of the invention by a Newreporter System 100 and arrangements. In the embodiment of claim 1, a Newreporter System 100 has and arrangements: a. At least one classification unit (130), which is designed to classify image data and / or image data streams, wherein at least one classification (132) takes place on the basis of or under the consideration of at least one client information item (120);

 b. wherein at least one client information (120) is associated with at least one client (110) that interacts with a news reporter system (100) over at least one computer network and that client (110) can send and / or receive image data.

Thus, the present invention is a Newreporter system 100 that allows classifying video or video data streams. Due to the variety of video transmitters or even video streams in general, it is possible that for different users 110, the same video streams have a different relevance. It may also be that for a user 110, depending on or by what means, for example a medium such as a notebook or a mobile phone, but also by which or which data networks he accesses a video / video streaming system or videos, the respective classification 132 considers the accessor. Thus, different classifications can be determined depending on the access means.

 Thus, as is known in the art, the classification 132 is not performed over fixed rules that are the same for all users. Rather, a Newreporter system 100 may honor client information 120 and, due to it, perform classifications 132 of video streams, even in combination with other classifications 132. This allows a particularly flexible classification 132 of videos and opens up the possibility of assessing the relevance of videos, since thus 132 client information 120 can be included in the classification. As a result, these may be e.g. particularly suit the particular client 110 who has requested a classification 132. This makes it possible to meaningfully arrange the unmanageable amount of videos or video streams that could not previously be surveyed.

 Client information / user information 120 is information that is related to one or more users / clients 110 or also to one or more devices, arrangements or methods. Client information 120 is hereby e.g. Data about or from users 110 or devices 110, devices 110 and method 110 itself. This may include, for example, passive data that may be in the profile of the user 110, such as a user's profile. As hometown, group memberships, friends or even data that have been revealed, for example, by analysis. Other types of user data may be active data. Active can mean that these data only exist at runtime and change very frequently. For example, the current coordinates of the user 110, e.g. GPS coordinates or access point, its IP, status message, connection speed, client type. Due to the characteristics of previously shown client information 120, further information can often be derived from such information. For example, in the location perimeter based on the access point, the GPS coordinates or / and an IP address. Such derivable information is itself also as

Client information 120 referred. In another aspect of the present invention, at least one client 110 has a camera or other means from which it can send image data over a computer network, eg, 141, 142, 140. Accordingly, video streams can be sent. This allows it

Video streams, also timely or live / recorded in real time streams, based on client information 120 classify. In doing so, such classifications 132 may also serve to clarify the relevance of streams to clients 110 e.g. judged by client information 120. This makes it possible, for example, to set rankings for ads.

 Additionally, in a further embodiment, at least one client information 120 may be transmitted over a computer network. This allows the client information 120 to be present not only in the Newreporter system 100, but rather that more sources can be used. For example, it is possible to use client information 120 from external systems, such as social networks, but also from clients 110 or in this or descriptive data thereof, in classification 132.

 Furthermore, the evaluation of at least one contact in the classification 132 can be used. Thus, among other things, it is possible that video streams are routed through friend networks. In this case, the distribution may function similar to a waterfall, as can be seen in Fig. 4a. This enables a particularly efficient distribution through social contacts of clients 110.

In addition to the previous variants, it is possible for the client information 120 of the geoinformation of the transmitter 110, as well as the receiver 110, to be used jointly for the classification 132. This makes it possible, for example, to classify the streams that are in the vicinity of the receiving client 110 as particularly interesting. In addition, if contact information that is part of the client information 120 is used, it is possible to perform other interesting classifications 132 by the combination. For example, the classification 132 based on the video streams of friends / contacts of a user on a social network who are in the vicinity of him and sending streams at the time of his access to the Newreporter System 100.

 A particularly preferred variant is that a Newreporter System 100 can have means that make it possible to perform speech analysis. This makes it possible to recognize spoken words or to listen to linguistic instructions. This analysis is particularly advantageous in combination with further analyzes which, for example, make it possible to carry out classifications 132 on the basis of this. Thus, for example, the relevance of terms for a stream can be determined, for example, the frequency of how often they are said.

Note that in addition it is still possible that classifications 132 need not be absolute. Therefore, it is possible that these probabilities or membership intensities may include at least one class. For example, a probability or membership intensity, eg by a percentage affiliation, can be specified. This may, for example, indicate the probability that the classification 132 applies and / or also in combination the intensity of a classification 132. For example, it is possible to determine the Intensity of at least one classification 132 to determine at least one stream. This is especially useful when using speech analysis. For example, here the frequency of how often a word is called can influence the likelihood that this can serve as a classification means or it can be used to determine the intensity by the frequency of the mention.

 The classifications may be used by Wetteren to influence presentations / advertisements. For example, which or which video streams are displayed. Such displays can occur, for example, in mobile phones or in notebooks. For example, by using client information 120, it may be that in a notebook, HD videos are given a higher relevance than on a mobile phone, and this is therefore reflected in the display.

 The present invention 100 further relates to a method for accessing documents and / or document parts stored in a document base, the method comprising the steps of: a. Receiving or retrieving client information (120), wherein at least one client information (120) is associated with at least one client (110), which interacts with a news reporter system (100) via at least one computer network (140), and that client (HO) image data and / or transmit and / or receive image streams; and b. Classifying (132) the image data or image data stream, wherein at least one classification (132) is based on or under consideration of the client information (120). Further advantageous embodiments of the method according to the invention can be found in the further dependent claims.

 Lastly, the present invention provides a computer program having instructions to perform any method described herein.

 4. Brief description of the drawings:

Fig. 1a: A news reporter system and arrangement according to an embodiment of the present invention;

 Fig. 1b: A classification unit and arrangement according to an embodiment of the present invention;

 Fig. 2: Method of a Newreporter system according to an embodiment of the present invention;

 3: interaction of a Newreporter system according to an embodiment of the present invention;

 4a, b: method and exemplary representation in evaluation by Klierten according to an embodiment of the present invention;

5a, b: Method for classification by speech recognition according to an embodiment of the present invention; Fig. 6: Editing video streams according to an embodiment of the present invention;

 5. Detailed description of preferred embodiments

Fig. 1a shows a news reporter system. The system uses state-of-the-art means for distributing the video streams (referred to as stream or video in the following, but also always applicable to image data or image data streams or the like) of one or more transmitting clients 110 in the entire invention one or more recipients 110 to mediate or to send directly. In this case, transmitter 110 and receiver in FIG. 1a are designated as clients 110, wherein clients 110 can also be transmitter 110 and receiver 110 simultaneously.

In order to better understand the invention, clients 110 will also be referred to as senders 110 and receivers 110 and not as sending and receiving clients 110. This will make it easier to see in what role a client 110 can be used but do not limit its capabilities or the capabilities of the invention 100. As can be seen in FIG. 1a, streams may be transmitted via various computer networks 140 or a combination thereof. For example, over wireless networks 141, such as WLAN, cellular, and in particular the Internet 142. The Newreporter System 100 has means for classifying a video stream, such as a classification unit 130. Through these, video streams and / or contents thereof can be differentiated Classes are assigned. In addition, the Newreporter System 100 may have other means used in the classification 132, such as e.g. Client information 120. These may e.g. be used by the classification unit 130 to achieve better results in the classifications, or to be able to classify centered for a client 110. Such client information 120 can occur in different systems, as well as in the Newreporter System 100 itself.

The Newreporter System 100 can still be associated with other systems or technologies 150. In this case, all of these systems or technologies 150

Own client information 120. For example, streams may be included on web pages 151 or other documents. Or vice versa, it is also possible that web pages 151 or other documents are included in streams. For example, visitors to a website 151 could create a video stream over this or information from the website 151 could be shown in a stream. It is also possible for external client information 120 to be accessed by such means, such as social networks. Also, a web site 151 that includes one or more streams may have client information 120. For example, their location, language, target audience, but also, for example, which clients 110 visit them generally or at the time of communication with the Newreporter System 100. This is also possible with web services 152. Thus, web services 152 can be offered or also consu- be miert. In addition, further external systems 153 are conceivable, for example web servers or programs that are executed on them, such as geoinformation systems, terminals or even televisions.

For example, documents may appear in a document base, also called a database, in which the documents are stored. An example of a document base is a file system. However, a document base may also be active, for example, the database / document base may be a web server, or multiple web servers, such as the Internet 142. The term database also refers to multiple systems or systems coupled over computer networks. The term document is therefore a collective term for all possible outputs of a database or else a compilation of data generated by a user 110. For example, a document may be dynamically generated from a database, which is why a database within the scope of the present invention is to be considered a source or combination of sources or source systems from which data may be requested, written and / or altered. A document is therefore a logical unit, a partition, component and / or subdivision and therefore also applies to parts of documents. Embodiments of the present invention can use the structure information of the database in order to improve and / or accelerate access to the database or documents occurring therein. For example, the following data and associated systems or systems can serve as a database and thus as documents: hypertext documents, Word documents, e-mails, web servers, program code such as classes or objects or other constructs that occur during programming or compiled source code generated therefrom , API calls or return values, access to program parts, business objects, such as documents or master data, application servers, SAP systems, data warehouses, text documents, images, audio files, social networks, videos, blogs, Twitter, social networks, mobile devices, such as cell phones, peer-to-peer networks, input devices, file systems, databases, search engines, servers, routers, machines, sensors, test systems, debuggers, people and / or automobiles. If the present invention is used in a computer network, this network and its participants can assume the role of the database, eg the Internet network itself, peer-to-peer networks, web servers, Internet sites, clients, mobile clients (eg mobile phones, notebooks , PDAs, etc.) and other actors. A web page 151 or web page identifies a document that is accessible over the Internet and may include various content that occurs there, such as hypertext documents, videos, images, and other documents that may include hyperlinks. The term website can also stand for several documents, eg for all or a part of the pages under a certain domain. Thus, the term website is also a collective term for what is generally called website or website, ie a collective term for an entire Internet presence, eg an appearance of a company, an organization, a private person, an association, an interest group or to a specific website Purpose, eg sale, trade, information, discussion, exchange, pleasure, search, mediation, etc. Such an internet site may have various Protocols such as TCP / IP, HTTP, HTTPS, FTP, POP3, SMTP and other protocols used for communication in computer networks.

Users 110 often use technical devices that communicate with computer networks 140. In addition, users 110 do not necessarily have to be humans. Rather, users 110 may be, for example, machines, apparatus and methods, including user groups. Often, users 110 also associate information, or even the technical devices that use them. Therefore, because a user 110 uses technical devices to communicate on computer networks, no further distinction is made between user 110 and client 110 and the word client 110 is used as equivalent to user 110, and vice versa. Therefore, client information 120 is also to be understood as information about user 110, as is the information about technical devices. For the purposes of the invention, e.g. Also, client information 120 may be transmitted through documents or even be one or more documents.

Client information 120 is information that is related to one or more clients 110. Thus, this client information 120 may relate, for example, to particular users 110 or user groups, or to their technical devices. This client information 120 may be, for example, passive data, for example, in the profile of the user, such. Hometown, group memberships, friends or even data that has been uncovered for example through analysis. Other types of user data may be active data. Active can mean that these data only exist at runtime and change very frequently. Often, it is also interesting to use data from the device that client 110 uses for classification 132. For example, like the current location of client 110 whose IP, device type, status message, connection speed, is client type. Due to the properties of previously shown client information 120, it is often possible to derive further information from such information. For example, in the location perimeter due to an IP address. Such derivable information is itself also referred to as client information.

Further, in such a system, at least certain client information 120 may be found that is particularly useful for classifications 132, such as positions. These can be used to represent the location of one or more sending clients 110 or even of receiving clients 110. Likewise, it is possible that they represent home locations of clients 110. Additionally or alternatively, known (marked) contacts, often friends, contacts, or the like in social networks, such as Facebook, Xing, o. Ä. appearing in the client information 120. As a result of that

Client information can also be addressed via computer networks, the information about known contacts, for example, via an external system can be revealed, such as the Open Social API. For example, it can be determined which Users 110 in other networks are friends, such as Facebook, Studivz, Mail Contacts, Google Mail, Twitter, Xing or Linkedin.

Thus, in principle, all information from one or more user profiles can also be used in combination. Client information 120 may also be in a stream itself, e.g. For example, the language or format of the stream and other information. For example, a sending client 110 or user 1 can speak during a recording and this language can represent client information 120.

Thus, a big difference to the prior art, since thus the

Client information 120 can be noted in the classification 132. As a result, it is not only possible to classify streams for all users 110 the same as was previously possible, as is the case, for example, with search functions used today. For example, it is possible to perform at least one classification 132 for relevance to clients 110.

1 b shows a possible embodiment of the classification unit 130. This has classification means 131 which make it possible to carry out classifications 132. In doing so, they may pay attention to client information 120 as displayed. It should be noted that except the

Of course, also normal classifications 132 can be performed with it. Through client information 120, new classifications 132, as well as new client information 120, may be determined, also taking into account normal classifications 132. Furthermore, classifications 132 can also originate from external systems or can also be stored in them. The means for classification 131 may be z. As apparatus, computer programs or even classification rules. It is also possible that at runtime new classification means are made available to the Newreporter System 100 or transmitted to this. Of course, there may also be the possibility of parameterizing existing rules and specifying assignments for the parameters.

For example, client 110 and hence user 110 could provide new classification rules or references to them, which will then be used by the Newreporter System 100 in the future. This information could, for example, be stored in a memory unit. These could also be used specifically for individual clients or client groups, and for such and other cases, the Newreporter System 100 may have specially specialized means.

FIG. 2 shows a method with which it is possible to implement a Newreporter System 100. In this case, client information 120 is accessed at least once in 201, such as receiving or retrieving the client information 120, and on the basis of which at least one video stream is classified 202. The individual steps 201, 202 can also be executed several times and it is possible to that according to classification 132, the prevailing This step is again performed, for example because the information has not yet been sufficient for a satisfactory classification 132.

 An extension of the method may also access normal classifications 132. Also, for example, by retrieving or receiving and use this in addition. The steps can be carried out in any order.

 In addition, it is possible that data, such as received or retrieved data, e.g. Client information 120 or classifications are stored in a persistent and / or volatile memory unit. This can be used to use them for re-classification operations.

It is also possible to implement each function disclosed in this invention also in combination with other functions in methods.

 The Newreporter System 100 has been shown in FIG. 1a as a central unit. However, it should be noted that the individual components do not necessarily have to occur in this arrangement. Rather, this is to be seen as an illustration. The components may also be present in other arrangements in order to ensure the best possible implementation of different scenarios. For example, classifications 132 may also be performed on clients 110. Note that, therefore, FIG. 1a and FIG. 2 are far from the only possible possibilities for realizing such a Newreporter system 100 or method or the associated arrangement. For example, it is also possible to realize such a system via a P2P network and, for example, to have no central servers. Or such a system, method or arrangement could be used in conjunction with Content Delivery Services. Furthermore, it is also possible that the Newreporter system 100 can be used only as an intermediary between transmitters 110 and receivers 110, as shown in Fig. 3. Thus, the Newreporter System 100, associated arrangements and methods, is much more than a description of various features that, in any possible arrangement, reveal possibilities that can be used in video platforms. Therefore, as the term Newreporter System 100 is referred to in this document, it is meant not only the corresponding apparatus, but also the associated methods and arrangements which may also facilitate the disclosed capabilities.

This flexibility is due to the fact that this invention 100 or group of inventions can be realized as computer-implemented systems or as computer programs. As a result, all the facts presented can be realized in different programming languages on different platforms. In addition, all procedures can be represented in declarative programs and thus in declarative situations, and vice versa. Likewise, the processes can be converted as apparatuses or arrangements and vice versa. In addition, due to the flexible nature of the invention, many of the individual parts of the invention discussed may also be combined or rearranged to provide better-speed solutions or other solutions. Therefore, the description of the invention is to be understood as an exemplary embodiment, the features of which may also occur in other arrangements, systems and methods.

 In addition, it should be noted that, for clarity, numerical reference is also made to Newreporter System 100, e.g. in Fig. La or Fig. 2 is referenced. For the purposes of the invention, however, all the arrangements and methods of this document would have to be referred to as the Newreporter System 100, but the clarity was omitted for the aforementioned reason.

 More preferably, such a Newreporter System 100 is used in computer networks, such as the Internet 142, and used together with the techniques employed therein. For example, multicasts can be used to distribute video streams particularly efficiently and to save bandwidth.

 Most preferably, Newreporter System 100 is used for distribution / delivery / classification 132 of livestreams. Under Livestream here is a small delayed delivery, d. h ie the timely delivery of recorded image data to other parts of the Newreporter system 100 understood. For example, videos are uploaded to YouTube and can be watched. A lifestream is e.g. still characterized in that several users 110 can "hook in" and see the same content, the time delays that take place between individual consumers, due to technical limitations come to terms and not, as in a video portal, by its function The Newreporter System 100 additionally has funds available that will stream such a livestream

Scenario, such as timeshift playback, which is now being used around receivers in television channels, to allow clients 110 to receive the streams and to lag behind "reality." Thus, it is possible that Not only can video streams be viewed when the stream is completely recorded or when the program is about to begin, much more, for example, clients 110 may already be starting to watch the beginning of streams, even if it is not yet completely broadcast.

 Most preferably, such a Newreporter System 100 is shared with a "normal video portal." This also allows new methods and teachings of this document to be transferred to them, and the functions that a Newreporter System 100 can provide complement such a video portal. Thus, it is possible, for example, recorded

Watch live streams through a conventional video portal, or use the classification features in a normal video portal.

Such a Newreporter System 100 can work with a variety of means that allow video streams to be streamed or consumed. For example, computers, surveillance cameras or other microchip-controlled devices. However, it is particularly preferred for mobile devices are used, which have at least one video camera. For example, mobile phones / smartphones, where, of course, several cameras can be used simultaneously or notebooks. Such devices are also particularly preferably via a wireless computer network 140, for example the Internet 142 and / or a Mobile network 141 connected to the Newreporter System 100 or with other clients. You can also be connected via a mobile network to the Internet 142.

 It should be noted that often scenarios are desirable in which more than one camera generates streams. For example, when reporting something, it is often desirable to see the face of the rapporteur at the same time as the normal image data. Modern mobile phones often have 2 cameras, such. Eg the Nokia N95. One is on the front and the other on the back. These could simultaneously generate streams. Thus, it would be possible with this or similar mobile phones to solve this problem. The Newreporter System 100 may have further specialized means for doing this, such as merging the two different image data sources as one stream. This is z. B. a functionality that can be performed on the client 110.

 Since modern mobile devices have beamer, it is also possible that the streams, or a stream consisting of several image data sources, are displayed in different parts of the receiving client 110. For example, the content that is being reported can be displayed via the beamer, and the reporter can be displayed via the mobile phone itself. Similar solutions are conceivable for other clients 110, such as mobile telephones.

 Due to the technical possibilities, other scenarios are conceivable as pure reporting. For example, the Newreporter System 110, with the ability to combine streams or output them on different channels, could also be used to enable videoconferencing. The streams from several mobile phones can be combined to capture at least one room or its parts. Due to the wide variety of playback options, the various mobile phones could also use their beamer to play different or a combined stream, at least one other room. These could, for example, come from another room in which, as in the first one, the streams are sent and received by different clients. Thus, "virtual meetings" would be conceivable.

 These other scenarios show that the Newreporter System 100, whose preferred use case is news, can be used for many more purposes. Thus, it is conceivable, except conferences about it, also z. For example, lectures or video chats in a novel application dimension.

 Note that even in such scenarios, based on classifications 132, it may be determined where, for example, which stream may be displayed.

This means that one or more advertisements from clients 110 can also be adapted on the basis of classifications 132, which can also include client information 120. For example, a receiver 110, when accessing the Newreporter system 100, first sees streams that correspond to at least one classification 132, preferring its client information 120. Or, based on at least one classification, the most relevant stream for the client 110 is displayed. For example, one friend's active stream or multiple streams from friends. This link between display and classifications, it is z. For example, it is possible to present vivid and clear video streams.

 This can also be used, for example, on a web page where, depending on which client 110 visits it, other streams are displayed. Or it is possible to observe the client information 120 in an ordinary search process and z. For example, because of which to sort the result set.

 A variant of the Newreporter system uses positions to make classifications 132. In doing so, at least one location associated with the stream is used, such as the location of the client 110 that creates the stream. This position could z. B. correspond to the current position of the transmitter and / or the home / home position of this. This can be z. For example, perform the following classifications 110: Which streams of broadcasters are located near the receiving client 110? Which streams are near the home location of the receiving client 110? Which streams have a home location near the home location of the receiver 110? Which streams have a near home location to the receiver 110 and are located by their current location near the current location of the receiver 110.

 Note that fuzzy logic may be used in particular for fuzzy indications of classifications 132 that are or have been determined. This could also be specified by "in close proximity", etc.

Further, a Newreporter System 100 may have specially optimized means for geocoordinate calculations known in the art.

 Also, a Newreporter System 100 may have means for speech recognition, it z. B. can be used to interpret speech in streams, or even user reactions, as well as can be used for voice control.

Another variant uses social data such as friend lists in the Newreporter System 100 or in external systems to classify. This allows, for example, to classify streams of contacts. As a result, for example, due to the contact strength, such as the chat or (e-) mail frequency can be classified as relevant or less relevant. In addition, z. For example, in a search, streams of contacts are considered to be particularly relevant.

 Particularly preferably, users 110 may also mark a stream as good or worth seeing or not worth seeing, e.g. Through interactions such as reviews, which may also be linguistic expressions. Such marking is referred to as rating below. Such an evaluation can also be carried out on the basis of other means, for example the user behavior / resp. Interpret client behavior. For example, it may be for

How long a user 110 views a stream can be used. The longer he follows the stream, the more interesting it seems to be. Due to such and other evaluations, which can also be understood as classifications 132, it is possible a new one Classification 132 together with client information 120 perform. For example: Which streams viewed by contacts were rated as interesting / worth seeing? Or which streams were rated as interesting or not at all by the contacts of the receiver 110? Which streams were rated as uninteresting?

Another possibility is a possibility of obvious recommendation of a stream. One such recommendation is called Forward. This may be, for example, a flag / tag that can be set by clients 110 to deliberately recommend the stream to contacts.

 It is as before possible that also forward information, d. H. Streams marked as good can be used for classification 132.

These or similar judgments allow a stream to propagate as in Fig. 4a. There, receivers are shown who receive a stream and perceive it as good, or give this forward or feel interesting. As a result, the stream spreads to other users who could feel him again as well. As a result, a rapid spread of video streams to probably interested users 110 is possible. This is shown abstractly in FIG. 4b. At least one client 110 rates at least one stream 411. Because of this, the stream is classified. For example, by rating as interesting or uninteresting. This allows the stream to be classified 410 for other clients 110. This may result in other clients 110 viewing and rating the stream 411, and thus may be reclassified 410 as well.

Streams may also be further classified by relevance or membership number into a class or a combination of different classifications 132 in their classification 132. For example, how much interested a stream contacts a user / client 110x? This can be done, for example, as seen in Figure 4a. The receiver 401 (a client 110) exemplifies that a stream is evaluated by several of its contacts / acquaintances (also clients 110) and thus e.g. the class is assigned interesting. This stream is thus perceived by two contacts / clients 110 as good and thus seems to be particularly relevant to the receiver 401. For example, for receiver 402, the stream is not as relevant. The first classification 132 is thus interesting and the further classification 132 is very interesting for one or more clients 110.

Please note that it is of course also possible to include further information. For example, negative ratings and / or location data may also be included. More preferably, it is possible to combine the previously described classifications 132 and associated means. For example, the classification 132, due to locations, and the classification 132, based on ratings, may be combined. For example, this may determine the following: Which streams near a client 110 have been rated particularly well? Are contacts 110 of a client 110 near and emitting video streams? Here are all other combinations that result from conceivable. A particularly interesting classification option 132, which, like all others in all conceivable combinations can be combined with the previously disclosed, is the classification 132 by language analysis, such. B. in Fig. 5a and b. In this case, by means known from the prior art, for example speech recognition apparatuses, what is said 501 in the stream or at the receiving client 110. After this recognition, at least one classification 132 is performed by recognized words 502. This can be done at runtime These classifications 132 can also change at runtime, and these classifications 132 can also be of different strength, and thus also be described by probability statements for correctness, which means that fuzzy logic can also be used.

 A particularly simple classification 132 by voice is the possibility that the sender 110 says certain keywords, after which he then names areas that the current stream is about.

 Another classification option is comments from recipients. For example, if a user 110 says "cool" or the like, the stream could be classified as very interesting.

 Another classification option is the word frequency in the stream itself. If a word is said very often, it seems to map a topic of the stream. In a simple example, each word said could be given a frequency and the frequency could represent the probability of the classification 132 being correct. It is of course conceivable that other rules or means are used, for example, to article or similar

Exclude language constructs. It could also be used speech analysis tools that analyze whole sentences and thus provide better results.

 Furthermore, it is also possible in such a system to use means which occur in the So-ad-tec system (EP 10001967). For example, schemes and means for classification described therein may be used to improve the classification and to determine categories. Because of this, the classification can also be broken down into hierarchical schemes, and it is possible to use not only classes in the classification, but also much more categories, taxonomies and other elements that occur in the schemas of a So-ad-tec system.

 More preferably, clients 110, transmitters 110 as well as receivers 110, destinations or target groups for a stream may also specify via various means. Such destinations may be, for example, areas on a map, locations with radii and one or more user groups or combinations thereof.

Therefore, a Newreporter System 100 may also have the ability to group users 110 into groups, or use groups in other systems, such as social networks. In this case, users 110 could also define group memberships themselves. Particularly preferably, advertisements can also be determined in or to a stream, or also presented to users. This can be enabled via known methods or systems. Particularly preferred for a So-ad-tec system or method is used, since 120 are used by this client information from transmitters and receivers, as well as classifications 132, and thus the best possible advertising can be determined.

 Another capability of the Newreporter system 100 is to allow people to spot objects or generally objects in streams that may also represent classifications 132. This can be done by technical apparatuses, as well as by user 110 or also be performed as a hybrid method. For example, through speech analysis. Certain key sets, e.g. are seen by broadcasters 110, such as "Here's the person XXX." Another possibility is that recipients 110 specify by voice, or by other means or a combination, which person they see in the stream For example, faces can be automatically recognized as such, and clients 110 can indicate which person to associate with the face, for example, automatic face recognition, as known by digital cameras, for example other animals, such as dogs and cats additionally recognized.

 Recognized objects can then except for pure classification 132 z. B. also directly in the stream or by additional information, such as by special presentations, be available. It is also conceivable that z. For example, products or other objects may be selectable on recorded streams, such as hyperlinks, Javascript, or similar technology.

 Most preferably, a Newreporter System 100 also has means that allow objects to be tracked in video. That is, although the camera or object is moving, it is possible that this "moving" object may still be known, for example because of the markers discussed above and in combination with engineering means, a user 110 may mark something that will be tracked further ,

 Of course, other means of image recognition can be used as a combination. For example, from face recognition, so that the user 110 can already be presented with a selection of who could be on a video stream.

Also can be used in a Newreporter system 100 swarm intelligence, such. For example, the particle swarm optimization (PSO, http://en.wikipedia.org/wiki/Particle_swarm_option) algorithm or one of its optimizations. This can z. B. can be used to track objects in videos.

These various abilities can be used to, for example, make it possible to enumerate all persons in a stream that occur in them. For example, if they are run over with the mouse or they could also be listed near the stream. For example, below or next to the stream ad. But it is also possible that in the case of over- a "preview window" is displayed, similar to the case, for example, in in-text advertising by http://www.vibrantmedia.de.

 Due to the classifications 132, a hyper adapter (EP09180953) can also be used as a search function.

Also, means 131 for classification can be used, which are trainable. It can

Client feedback can be used to train them. For example, a client is shown 110 streams that may interest him. If he marks a stream as uninteresting, this can lead to the learning effect that the client 110 no longer receives this or similar streams. In addition, algorithms from the field of swarm intelligence can be used as means for classification 131. For example, mechanisms of a So-ad-tec system can be used to determine which streams for at least one client 110 may be advertised as interesting.

 Further, it is possible for clients 110 to mark other clients 110, e.g. For example, which sending clients 110 do not interest them or who rate them as good. This can then be used for further classifications 132.

 Also, the Newreporter System 100 may have means for displaying subtitles in streams. These can be calculated directly in a stream, but can also be delivered separately, so that they can only be displayed in a receiver via the stream or at another location. Possibilities for such implementations are known from the prior art. The creation of the transcription itself can be implemented by means for speech recognition from the prior art. In this case, such means for speech recognition can be installed and used on the client 110 in the Newreporter System 100 or in other devices.

 Furthermore, a So-ad-tec system can work with a variety of video compression methods. It may also have the ability to convert video streams to another format. This can be z. For example, it can be used to convert a stream into appropriate codecs for clients 110.

 Also, a Newreporter System 100 can support editing of video streams. It is also possible to perform timely operations, such as live soundtracking (a new soundtrack for a stream), live editing, composition of different streams, or similar operations. It is also possible to switch such operations one after the other. This means that the result of one operation can serve as input for the next one. For example, different streams are cut together and the resulting stream is then re-voiced or otherwise voiced.

In Fig. 6 it is shown how different streams of transmitters such as 601/110 have a new one

Stream / Sender 603/110 can be generated. This result is, so to speak, a "virtually" sending client 110 and therefore has the same properties as a normal client 110 itself. It has the Newreporter System 100 means for cutting and joining and switching between streams, the z. B. by a client 602/150/110 can be operated. The client 110 is also characterized by 150 and 602, since this may also be an external system, but also a normal client 110 or another other means for post processing, such as computer programs, systems, arrangements or apparatuses.

The structure in Fig. 6 enables reporting as it is known from television, with the difference that it can be adapted by normal users. For example, people film a sporting event live. Their streams are then sliced together as a resulting stream in a "virtual" client 110, depending on the perspective In Figure 6, the resulting stream / sender 603 is also seen as another sender, which again might have its own properties during post-processing 602, copied from the source stream, or even determined by the means that perform the post-processing, so that stream 603 itself can have client information 120, and all the operations described above are applicable to it as well.

Due to the fact that with such post-processing also the further functions of the

 Newreporter Systems 100 can be used, many advantages in post-processing can be used. For example, the positions of the transmitters 110 may be used. Or as interesting marked streams can be composed together.

 Due to the fact that nowadays all recordings are made with digital devices that can use eg CCD chips or the like for digitization whose properties are used to support the Newreporter System 100 also night shots, similar to a night vision device. This can be realized, for example, that all CCD chips actually absorb infrared light and the associated wavelengths are filtered out during normal recording. Using a Newreporter System 100, this information can be used to either use this information in Client 110 or the Newreporter System 100 itself or to combine it with the other image data in order to obtain usable streams even at night.

 Thus, a Newreporter System 100 may have the ability to augment video streams, such as through IR information. It is possible, however, that a Newreporter System 100 also has other means of improving the quality of video streams. For example, it is known that fast pans or jiggers of the camera are disturbing viewers. Therefore, the stream can be corrected promptly by anti-joggers, for example. This can be done for example by software filter. For example, the stream size can be artificially reduced to intercept software anti-jitter shakiness, which would normally cause new areas to appear in the image. In general, algorithms can be used which improve the quality of the video stream at least subjectively for the viewer.

Similar to the night vision option, a Newreporter System 100 can also support 3D streams. In this case, a client 110, for example, via two cameras, at an eye relief from one another, use it simultaneously to create a 3D stream or send both streams to the Newreporter System 100, which then calculates a 3D stream. It can also support other techniques that can be used to create 3D recordings. The Newreporter System 100 may have additional means for such cases, which are optimized especially for this application. For example, information about the 3D representation can be added to a stream or sent out separately.

 Furthermore, a Newreporter System 100 can support cryptographic means. These can be used, for example, to encrypt streams between client 110 and the Newreporter system 100 or even between clients 110 themselves. Both asymmetric and symmetrical methods can be used. For example, RSA, AES and other well-known.

Also, a Newreporter System 100 has the ability to use "real world" barcodes, such as http://en.wikipedia.org/wiki/Strichcode, and most preferably 2-D codes, which can be used to position items or to refer to objects, or to refer to streams, and there is the advantage that objects of the real world, which are already "tagged" by such barcodes, can be easily determined.

 Another place of use of such barcodes may be the reference to a stream or even to streams of a client 110 or also to post-processed streams by such a barcode. This has the advantage that users 110 can easily publish their streams in the real world, for example on a business card, due to such barcodes. If somebody scans the business card, it receives the address of the stream.

 Also, such a Newreporter System 100 may have the ability for each client 110 and stream, as well as post-processed streams, to be reachable through a unique address, which makes it easy to reference them. This can be implemented, for example, via a URL.

Also, such a system may have a billing unit that allows broadcasters to be involved in the advertising revenue generated by their streams by measuring the impact of advertising by various means. For example, how many users 1 click on a stream in a stream. Advertising can be z. B. be used by a So-ad-tec system.

If streams are viewed in a web browser, known means can be used for this purpose. For example, the HTML Video Tag, or Adobe Flash or Silverlight.

An extension of the Newreporter System 100 connects maps with streams. Such a connection can be used for display as well as for analysis. For example, at which time in a geographic region particularly many streams are started. This could, for example, indicate a natural disaster. Also, for streams, a method similar to US2008 / 0126226A1 (http://www.mirriad.com/) may be used as an advertising system, but it allows advertising to be used in timely delivered streams.

 A Newreporter System 100 can also be implemented as a plug-in for social networks, eg. For Facebook via its public interface or for others, by using the Open Social API.

 In addition to all the features mentioned above, the Newreporter System 100 has means that allow users to classify themselves 10 videos / video streams or even clients 110. For example through tags.

Another function is that video streams or their sending clients 110 as well as receiving clients 110 can change their positions during runtime. In such cases, a news reporter may have specialized resources. For example, the changed position can be stored in the stream. Or, the display of the receiving client 110 is always adjusted based on its current position or current stream positions. Other additional functions could also be present, such as the user 110 being shown the video stream in a map and changing his position there due to the movement.

Claims

claims  Bin Newrcporter system (100) and / or arrangements for classifying image data and / or image data streams, in particular timely distributed image data, which are distributed via at least one computer network (140), the Newreportcr system (100) or an arrangement comprising:  a. At least one classification unit (130), which is designed to classify image data and / or image data streams, wherein at least one classification (132) takes place on the basis of or under the consideration of at least one client information item (120);  b. wherein at least one client information (120) is associated with at least one client (110) that interacts with a news reporter system (100) over at least one computer network and that client (110) can send and / or receive image data.  A Newrcporter system (100) or the arrangement of claim 1, wherein at least one client (110) has at least one camera and / or at least one means for delivering image data over at least one computer network (140).  A news reporter system (100) or the arrangements of claim 1 or 2, wherein at least one client information (120) is transmitted over at least one computer network (140).  A news reporter system (100) or an arrangement according to any one of the preceding claims, wherein at least one classification (132) serves to determine the relevance of at least one image data stream and / or image data for at least one client (110). A Newrcporter system (100) or an arrangement according to any one of the preceding claims, wherein at least one classification (132) of at least one image data stream and / or image data, client formations (120) containing at least one rating of at least one contact of at least one client (110), uses.  A Newrcporter system (100) or an arrangement according to one of the preceding claims, wherein at least one classification (132) of at least one image data stream and / or image data, client information (120), the at least one position of at least one sending client (110) and at least one receiving Contain clients (110). A news reporter system (100) or the arrangement of claim 6, wherein additionally the client information (120) is used, which contacts at least one image data stream and / or generate or generate image data from near the consuming client (110).  8. A news reporter system (100) or an arrangement according to any one of the preceding claims, wherein the system has means for spraysanalysc,  9. A news reporter system (100) or the arrangement of claim 8, wherein the classifier (132) can make classifications based on speech analysis or its results.  10. A Newreporter system (100) may comprise the arrangements of claim 8 or 9, wherein the language attribute includes means for assessing the relevance of words or consequent classification (132).  11. A news reporter system (100) or the arrangement of claim 10, wherein the relevance is determined based on frequency.  12. A newsreporter system (100) or an arrangement according to one of the preceding claims, wherein at least one classification (132) is given or determined with at least one probability of its application.  A new reporter system (100) or an arrangement according to any one of the preceding claims, wherein at least one display / presentation is adapted to at least one client (110) based on at least one classification (132).  14. A method for classifying bi-data and / or image data streams, the method comprising the steps of:  a. Receiving or retrieving product information (120), wherein at least one client information (120) is associated with at least one client (110) interacting with a news reporter system (100) above at least one computer network (140), and said client (110) Send and / or receive image data and / or image streams;  b. Classification (132) of the image data or image data streams, wherein at least one classification (1 2) takes place on the basis of or under consideration of the client information (120).  15. A computer program having instructions for carrying out a method according to any one of the preceding claims 13-14.