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CN110908566A - Information processing method and device - Google Patents

Information processing method and device Download PDF

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Publication number
CN110908566A
CN110908566A CN201811089795.2A CN201811089795A CN110908566A CN 110908566 A CN110908566 A CN 110908566A CN 201811089795 A CN201811089795 A CN 201811089795A CN 110908566 A CN110908566 A CN 110908566A
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image
target
feature
matrix
control
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张龙
文旷瑜
连园园
宋德超
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Gree Electric Appliances Inc of Zhuhai
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Gree Electric Appliances Inc of Zhuhai
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    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0484Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range

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Abstract

本发明公开了一种信息处理方法及装置。其中,该方法包括:通过图像采集装置对目标对象进行拍照得到目标图像;从所述目标图像中提取所述目标对象的特征图像,所述特征图像包括所述目标对象的动作特征;使用第一模型对所述特征图像进行分析,确定所述目标对象的特征图像所对应的控制参数,其中,所述第一模型为使用多组数据通过机器学习训练出的,所述多组数据中的每组数据均包括:特征图像和特征图像对应的控制参数;基于所述控制参数,控制相应的目标设备。本发明解决了由于现有的家用智能电器是根据用户的语音或遥控器对电器进行控制造成的控制动作有延迟、效率低的技术问题。

Figure 201811089795

The invention discloses an information processing method and device. Wherein, the method includes: photographing a target object by an image acquisition device to obtain a target image; extracting a feature image of the target object from the target image, the feature image including the action feature of the target object; using the first The model analyzes the feature image to determine the control parameters corresponding to the feature image of the target object, wherein the first model is trained by using multiple sets of data through machine learning, and each of the multiple sets of data is trained by machine learning. The group data includes: a characteristic image and a control parameter corresponding to the characteristic image; based on the control parameter, the corresponding target device is controlled. The present invention solves the technical problems of delayed control action and low efficiency caused by the existing intelligent household electrical appliances that control the electrical appliances according to the user's voice or a remote controller.

Figure 201811089795

Description

Information processing method and device
Technical Field
The invention relates to the field of equipment control, in particular to an information processing method and device.
Background
With the development of artificial intelligence technology, the perception user interface becomes one of the research focuses in the field of human-computer interaction, and is a highly interactive and multi-channel user interface taking interaction activities between people and between people and the real world as a prototype, and the goal of the perception user interface is to enable the consistency of human-computer interaction and human-real world interaction to achieve an intuitive and natural interaction boundary, so as to realize a human-computer interface with human center, namely, a computer can adapt to the natural interaction habits of people in the human-computer interaction process, but not to require people to adapt to the specific operation requirements of the computer.
The existing household intelligent electric appliances are generally controlled according to the voice of a user or a remote controller, the control action is delayed, the efficiency is low, and the intelligent degree is low.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides an information processing method and device, which at least solve the technical problems of delay and low efficiency of control action caused by the fact that the existing household intelligent electric appliance controls the electric appliance according to voice of a user or a remote controller.
According to an aspect of an embodiment of the present invention, there is provided an information processing method including: photographing a target object through an image acquisition device to obtain a target image; extracting a characteristic image of the target object from the target image, wherein the characteristic image comprises action characteristics of the target object; analyzing the characteristic image by using a first model, and determining a control parameter corresponding to the characteristic image of the target object, wherein the first model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the characteristic image and the control parameter corresponding to the characteristic image; and controlling the corresponding target equipment based on the control parameters.
Optionally, the extracting the feature image of the target object from the target image includes: establishing a matrix sampling channel; processing the target image according to the matrix sampling channel to obtain a characteristic matrix of the target image; and recombining the characteristic matrix into the characteristic image.
Optionally, the processing the target image according to the matrix sampling channel, and acquiring the feature matrix of the target image includes: sampling the target image through a sampling window to obtain sampling data; and carrying out different parameter processing on the matrix sampling channels with different sampling data to obtain the characteristic matrix.
Optionally, the controlling the corresponding target device based on the control parameter includes: generating a control instruction according to the control parameter; and sending the control instruction to the target equipment to control the target equipment.
Optionally, the target device comprises a household appliance.
According to another aspect of the embodiments of the present invention, there is also provided an information processing apparatus including: the camera is used for photographing a target object to obtain a target image; a processor for extracting a feature image of the target object from the target image, wherein the feature image comprises an action feature of the target object; analyzing the characteristic image by using a first model, and determining a control parameter corresponding to the characteristic image of the target object, wherein the first model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the characteristic image and the control parameter corresponding to the characteristic image; and the controller is used for controlling the corresponding target equipment based on the control parameters.
Optionally, the processor is configured to perform the following steps to extract a feature image of the target object from the target image: establishing a matrix sampling channel; processing the target image according to the matrix sampling channel to obtain a characteristic matrix of the target image; and recombining the characteristic matrix into the characteristic image.
Optionally, the processor is configured to execute the following steps to process the target image according to the matrix sampling channel, so as to obtain a feature matrix of the target image: sampling the target image through a sampling window to obtain sampling data; and carrying out different parameter processing on the matrix sampling channels with different sampling data to obtain the characteristic matrix.
Optionally, the controller is configured to perform the following steps to control the corresponding target device based on the control parameter: generating a control instruction according to the control parameter; and sending the control instruction to the target equipment to control the target equipment.
Optionally, the target device comprises a household appliance.
In the embodiment of the invention, the target object is photographed by an image acquisition device to obtain a target image; extracting a characteristic image of the target object from the target image, wherein the characteristic image comprises action characteristics of the target object; analyzing the characteristic image by using a first model, and determining a control parameter corresponding to the characteristic image of the target object, wherein the first model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the characteristic image and the control parameter corresponding to the characteristic image; based on control parameter, the mode of controlling corresponding target device gathers user's action through image acquisition device, and extract the characteristic image, carry out the analysis to the characteristic image with using first model, corresponding target device is controlled based on the control parameter who obtains, not only can save the vexation of using the remote controller, and can promote the purpose of human-computer interaction's experience, thereby realized promoting the human-computer interaction rate of accuracy, the technological effect of the fault rate among the reduction human-computer interaction, and then solved because current domestic intelligent electrical apparatus controls the control action that causes according to user's pronunciation or remote controller to electrical apparatus and has postponed, the technical problem of inefficiency.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow diagram illustrating an alternative information processing method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an alternative information processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided a method embodiment of an information processing method, it should be noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
Fig. 1 is an information processing method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
and S102, photographing a target object through an image acquisition device to obtain a target image.
Step S104, extracting the characteristic image of the target object from the target image.
Wherein the feature image includes an action feature of the target object.
Optionally, the extracting the feature image of the target object from the target image includes: establishing a matrix sampling channel; processing the target image according to the matrix sampling channel to obtain a characteristic matrix of the target image; and recombining the characteristic matrix into the characteristic image.
Wherein the processing the target image according to the matrix sampling channel to obtain the feature matrix of the target image includes: sampling the target image through a sampling window to obtain sampling data; and carrying out different parameter processing on the matrix sampling channels with different sampling data to obtain the characteristic matrix.
And S106, analyzing the characteristic image by using a first model, and determining a control parameter corresponding to the characteristic image of the target object.
Wherein the first model is trained by machine learning using a plurality of sets of data, each of the plurality of sets of data comprising: the characteristic image and the control parameter corresponding to the characteristic image.
And step S108, controlling the corresponding target equipment based on the control parameters.
Wherein the target device comprises a household appliance.
Optionally, the controlling the corresponding target device based on the control parameter includes: generating a control instruction according to the control parameter; and sending the control instruction to the target equipment to control the target equipment.
Through the steps, the actions of the user are collected through the image collecting device, the characteristic images are extracted, the characteristic images are analyzed through the first model, corresponding target equipment is controlled based on the obtained control parameters, the trouble of using a remote controller can be saved, and the purpose of experience of human-computer interaction can be improved, so that the technical effects of improving the accuracy of the human-computer interaction and reducing the error rate in the human-computer interaction are achieved, and the technical problems that the control actions caused by the fact that the existing household intelligent electric appliance is controlled according to the voice of the user or the remote controller are delayed and low in efficiency are solved.
In this embodiment, when the household appliance is controlled, the image acquisition device acquires the motion of the user, the acquired target picture is subjected to feature image extraction, a model is established by using a deep learning method, the parameters are input into the model, the model is trained, the target picture is input by using the model, the feature picture is extracted, the control parameters of the household appliance are output, and the household appliance is controlled by generating a control instruction according to the control parameters of the household appliance. For example, the air conditioner may determine, from the movement and posture of the user, whether the user needs to change the temperature of the air conditioner to be raised or lowered.
When the characteristic image is obtained, a matrix sampling channel is established, the target image is processed according to the matrix sampling channel to obtain a characteristic matrix of the target image, then the characteristic matrix is recombined into the characteristic image, different parameters of the target image are processed through different matrix sampling channels, and the obtained parameters are processed through a convolution network model to obtain a final characteristic image. The control gesture or the control posture of the user is recognized according to the image recognition technology, so that the user can control the smart home through fixing the gesture or the action posture.
In the information processing method of the embodiment, the actions of the user are collected through the image collecting device; extracting characteristic images of the collected target pictures; establishing a model by using a deep learning method, and training the model; and inputting the extracted features of the target picture into the model, and outputting control parameters of the household appliance. The trouble of using a remote controller can be saved, the experience of human-computer interaction can be improved, the accuracy of the human-computer interaction is greatly improved, and the error rate in the human-computer interaction is effectively reduced. The technical problems that the existing household intelligent appliance is backward in control mode, delayed in control action and low in efficiency are effectively solved.
Example 2
According to an embodiment of the present invention, there is provided an embodiment of an information processing apparatus, and fig. 2 is an information processing apparatus according to an embodiment of the present invention, as shown in fig. 2, the apparatus including:
the camera 20 is used for photographing a target object to obtain a target image;
a processor 22, which extracts a characteristic image of the target object from the target image, wherein the characteristic image comprises the action characteristic of the target object; analyzing the characteristic image by using a first model, and determining a control parameter corresponding to the characteristic image of the target object, wherein the first model is trained by using multiple groups of data through machine learning, and each group of data in the multiple groups of data comprises: the characteristic image and the control parameter corresponding to the characteristic image;
and a controller 24 for controlling the corresponding target device based on the control parameter.
Optionally, the processor is configured to perform the following steps to extract a feature image of the target object from the target image: establishing a matrix sampling channel; processing the target image according to the matrix sampling channel to obtain a characteristic matrix of the target image; and recombining the characteristic matrix into the characteristic image.
Optionally, the processor is configured to execute the following steps to process the target image according to the matrix sampling channel, so as to obtain a feature matrix of the target image: sampling the target image through a sampling window to obtain sampling data; and carrying out different parameter processing on the matrix sampling channels with different sampling data to obtain the characteristic matrix.
Optionally, the controller is configured to perform the following steps to control the corresponding target device based on the control parameter: generating a control instruction according to the control parameter; and sending the control instruction to the target equipment to control the target equipment.
Optionally, the target device comprises a household appliance.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (10)

1.一种信息处理方法,其特征在于,包括:1. an information processing method, is characterized in that, comprises: 通过图像采集装置对目标对象进行拍照得到目标图像;The target image is obtained by taking pictures of the target object through the image acquisition device; 从所述目标图像中提取所述目标对象的特征图像,所述特征图像包括所述目标对象的动作特征;extracting a feature image of the target object from the target image, the feature image including the action feature of the target object; 使用第一模型对所述特征图像进行分析,确定所述目标对象的特征图像所对应的控制参数,其中,所述第一模型为使用多组数据通过机器学习训练出的,所述多组数据中的每组数据均包括:特征图像和特征图像对应的控制参数;Use a first model to analyze the feature image, and determine the control parameters corresponding to the feature image of the target object, wherein the first model is trained by using multiple sets of data through machine learning, and the multiple sets of data Each set of data in includes: characteristic images and control parameters corresponding to characteristic images; 基于所述控制参数,控制相应的目标设备。Based on the control parameters, the corresponding target device is controlled. 2.根据权利要求1所述的方法,其特征在于,所述从所述目标图像中提取所述目标对象的特征图像包括:2. The method according to claim 1, wherein the extracting the feature image of the target object from the target image comprises: 建立矩阵采样通道;Create a matrix sampling channel; 按照所述矩阵采样通道对所述目标图像进行处理,获取所述目标图像的特征矩阵;Process the target image according to the matrix sampling channel to obtain a feature matrix of the target image; 将所述特征矩阵重组为所述特征图像。Recombining the feature matrix into the feature image. 3.根据权利要求2所述的方法,其特征在于,所述按照所述矩阵采样通道对所述目标图像进行处理,获取所述目标图像的特征矩阵包括:3. The method according to claim 2, wherein the processing of the target image according to the matrix sampling channel, and obtaining the feature matrix of the target image comprises: 通过采样窗口对所述目标图像进行采样,得到采样数据;Sampling the target image through a sampling window to obtain sampling data; 将所述采样数据不同的矩阵采样通道进行不同的参数处理,得到所述特征矩阵。The feature matrix is obtained by performing different parameter processing on different matrix sampling channels of the sampling data. 4.根据权利要求1所述的方法,其特征在于,所述基于所述控制参数,控制相应的目标设备包括:4. The method according to claim 1, wherein the controlling the corresponding target device based on the control parameter comprises: 根据所述控制参数生成控制指令;generating a control instruction according to the control parameter; 将所述控制指令发送至所述目标设备以控制所述目标设备。The control instruction is sent to the target device to control the target device. 5.根据权利要求1至4中任一项所述的方法,其特征在于,所述目标设备包括家用电器。5. The method according to any one of claims 1 to 4, wherein the target device comprises a household appliance. 6.一种信息处理装置,其特征在于,包括:6. An information processing device, comprising: 摄像头,用于对目标对象进行拍照得到目标图像;The camera is used to take pictures of the target object to obtain the target image; 处理器,从所述目标图像中提取所述目标对象的特征图像,所述特征图像包括所述目标对象的动作特征;使用第一模型对所述特征图像进行分析,确定所述目标对象的特征图像所对应的控制参数,其中,所述第一模型为使用多组数据通过机器学习训练出的,所述多组数据中的每组数据均包括:特征图像和特征图像对应的控制参数;a processor, extracting a feature image of the target object from the target image, the feature image including the action feature of the target object; using the first model to analyze the feature image to determine the feature of the target object Control parameters corresponding to the images, wherein the first model is trained by using multiple sets of data through machine learning, and each set of data in the multiple sets of data includes: feature images and control parameters corresponding to the feature images; 控制器,基于所述控制参数,控制相应的目标设备。The controller, based on the control parameter, controls the corresponding target device. 7.根据权利要求6所述的装置,其特征在于,所述处理器用于执行以下步骤从所述目标图像中提取所述目标对象的特征图像:7. The apparatus according to claim 6, wherein the processor is configured to perform the following steps to extract the feature image of the target object from the target image: 建立矩阵采样通道;Create a matrix sampling channel; 按照所述矩阵采样通道对所述目标图像进行处理,获取所述目标图像的特征矩阵;Process the target image according to the matrix sampling channel to obtain a feature matrix of the target image; 将所述特征矩阵重组为所述特征图像。Recombining the feature matrix into the feature image. 8.根据权利要求7所述的装置,其特征在于,所述处理器用于执行以下步骤按照所述矩阵采样通道对所述目标图像进行处理,获取所述目标图像的特征矩阵:8. The device according to claim 7, wherein the processor is configured to perform the following steps to process the target image according to the matrix sampling channel, and obtain a feature matrix of the target image: 通过采样窗口对所述目标图像进行采样,得到采样数据;Sampling the target image through a sampling window to obtain sampling data; 将所述采样数据不同的矩阵采样通道进行不同的参数处理,得到所述特征矩阵。The feature matrix is obtained by performing different parameter processing on different matrix sampling channels of the sampling data. 9.根据权利要求6所述的装置,其特征在于,所述控制器用于执行以下步骤基于所述控制参数,控制相应的目标设备:9. The apparatus according to claim 6, wherein the controller is configured to perform the following steps to control the corresponding target device based on the control parameters: 根据所述控制参数生成控制指令;generating a control instruction according to the control parameter; 将所述控制指令发送至所述目标设备以控制所述目标设备。The control instruction is sent to the target device to control the target device. 10.根据权利要求6至9中任一项所述的装置,其特征在于,所述目标设备包括家用电器。10. The apparatus according to any one of claims 6 to 9, wherein the target device comprises a household appliance.
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