WO2019119747A1

WO2019119747A1 - Behavior prediction systems and methods

Info

Publication number: WO2019119747A1
Application number: PCT/CN2018/091419
Authority: WO
Inventors: Seng Fook LEE; Zhaoyun WANG
Original assignee: Guangdong Grandeur International Exhibition Group Co Ltd
Current assignee: Guangdong Grandeur International Exhibition Group Co Ltd
Priority date: 2017-12-22
Filing date: 2018-06-15
Publication date: 2019-06-27
Anticipated expiration: 2020-06-22
Also published as: CN108346084A

Abstract

A behavior prediction system comprising: a data capture module configured to capture data including at least one of a movement of a buyer of a product/service displayed in a place, one or more gestures of the buyer while viewing of a virtual 3D display of the place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; an analysis module configured to analyze the captured data; and a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis in real-time.

Description

BEHAVIOR PREDICTION SYSTEMS AND METHODS

TECHNICAL FIELD

The presently disclosed embodiments relate to the field of three-dimensional (3D) imaging systems. More specifically, embodiments of the present disclosure relate to systems and methods for enabling a seller of product/service to predict a behavior of a buyer viewing a virtual 3D display of a place.

BACKGROUND

Many exhibitions happen these days about different type of items and arts. For many people, exhibitions are a good way for demonstrating their skills. An exhibition can be a demonstration or public display of works of arts, items of interest that may be held in a museum or an art gallery, or at a trade fair. Usually these exhibitions have a fixed venue and fixed timings. Further, most of the exhibitions have a limit on maximum number of people who can come to see the exhibitions due to many limitations such as a size of the venue, timing, and so forth. Further, people also have their limitations like timing of the exhibition doesn’t suits them, or may be venue for the exhibition is far from their location. Therefore, many people who would want to view the exhibition sometimes are not able to view it due to these limitations. Also when people visit a place or an exhibition physically, then looking at the large number of people in the place, it becomes difficult to understand preference, interest of the people. Sometimes, the buyer may want to know more information or buy a product/service displayed in the exhibition. Currently, there are no means for interacting while being in a virtual 3D display.

SUMMARY

In light of above, there exist need for providing techniques for predicting a behavior of a buyer or viewer watching a virtual 3D display of a place.

The present disclosure provides a system for enabling a seller of product/service to predict a behavior of a buyer in a virtual 3D display of a place.

The present disclosure provides a system for enabling a seller of product/service to predict a behavior of a buyer in a virtual 3D display of a place in real-time.

The present disclosure provides a method for enabling a seller of product/service to predict a behavior of a buyer viewing a virtual 3D display of a place. The behavior may be predicted in real-time.

The present disclosure provides an artificial intelligence system for a seller to predict a behavior of a buyer of a product/service.

The present disclosure provides a method for enabling a seller of product/service to predict a behavior of a buyer of product/service viewing a virtual 3D display of a place based on one or more parameters. The one or more parameters may comprise a purchase history of the buyer, type of products buyer liked, gestures of the buyer, current preference of the buyer, and so forth. The behavior may be predicted in real-time.

The present disclosure provides a virtual reality based system for enabling a seller of product/service to predict a behavior of a buyer of product/service viewing a virtual 3D display of a place based on one or more parameters. The one or more parameters may comprise a purchase history of the buyer, type of products buyer liked, gestures of the buyer, current preference of the buyer, and so forth. The behavior may be predicted in real-time.

The present disclosure provides an augmented reality based system for enabling a seller of product/service to predict a behavior of a buyer of product/service viewing a virtual 3D display of a place based on one or more parameters. The one or more parameters may comprise a purchase history of the buyer, type of products buyer liked, gestures of the buyer, current preference of the buyer, and so forth. The behavior may be predicted in real-time.

The present disclosure provides a web-based system for enabling a seller of product/service to predict a behavior of a buyer of product/service viewing a virtual 3D display of a place based on one or more parameters. The one or more parameters may comprise a purchase history of the buyer, type of products buyer liked, gestures of the buyer, current preference of the buyer, and so forth. The behavior may be predicted in real-time.

The present disclosure provides an augmented reality based system for enabling a seller of product/service to predict a behavior of a buyer of product/service viewing a virtual 3D display of a place such as an exhibition, a concert, and so forth.

An embodiment of the present disclosure provides system for predicting a behavior of a buyer in a virtual three-dimensional (3D) display, the system comprising: a data capture module configured to capture at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; an analysis module configured to analyze captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis..

According to an aspect of the present disclosure, the behavior is predicted in real-time.

Another embodiment of the present disclosure provides a behavior prediction system comprising: a data capture module configured to capture at least one of a movement of a buyer of a product/service displayed in a place, one or more gestures of the buyer while viewing of a virtual 3D display of the place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; an analysis module configured to analyze the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place in real-time; and a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis in real-time.

Another embodiment of the present disclosure provides a system for enabling a seller of a product/service to predict a behavior of a buyer viewing a virtual three-dimensional (3D) display, the system comprising: a data capture module configured to capture at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; an analysis module configured to analyze captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis.

Another embodiment of the present disclosure provides a method for predicting a behavior of a buyer in a virtual three-dimensional (3D) display, the system comprising: capturing at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis.

A further embodiment of the present disclosure provides a method for behavior prediction comprising: capturing at least one of a movement of a buyer of a product/service displayed in a place, one or more gestures of the buyer while viewing of a virtual 3D display of the place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place in real-time; and predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis in real-time.

A yet another embodiment of the present disclosure provides a method for enabling a seller of a product/service to predict a behavior of a buyer viewing a virtual three-dimensional (3D) display, the system comprising: capturing at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place; analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis.

According to an aspect of the present disclosure, the method includes identifying one or more patterns of buyer behavior while viewing the virtual 3D display

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the present invention are described with reference to the following drawings. In the drawings, like reference numerals refer to like parts throughout the various figures unless otherwise specified.

For a better understanding of the present invention, reference will be made to the following Detailed Description, which is to be read in association with the accompanying drawings, wherein:

FIG. 1 illustrates an exemplary environment where various embodiments of the present disclosure may function;

FIG. 2 illustrates a block diagram depicting various system elements of an exemplary behavior prediction system, in accordance with various embodiments of the present disclosure; and

FIG. 3 illustrates a flowchart of a method for predicting behavior of a buyer in a virtual 3D display/environment, in accordance with an embodiment of the present disclosure.

The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to) , rather than the mandatory sense (i.e., meaning must) . To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures.

DETAILED DESCRIPTION

The presently disclosed subject matter is described with specificity to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or elements similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the term “step” may be used herein to connote different aspects of methods employed, the term should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described.

Reference throughout this specification to “a select embodiment” , “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the disclosed subject matter. Thus, appearances of the phrases “a select embodiment” “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily referring to the same embodiment.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided, to provide a thorough understanding of embodiments of the disclosed subject matter. One skilled in the relevant art will recognize, however, that the disclosed subject matter can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosed subject matter.

All numeric values are herein assumed to be modified by the term “about, ” whether or not explicitly indicated. The term “about” generally refers to a range of numbers that one of skill in the art would consider equivalent to the recited value (i.e., having the same or substantially the same function or result) . In many instances, the terms “about” may include numbers that are rounded to the nearest significant figure. The recitation of numerical ranges by endpoints includes all numbers within that range (e.g., 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and 5) .

As used in this specification and the appended claims, the singular forms “a, ” “an, ” and “the” include or otherwise refer to singular as well as plural referents, unless the content clearly dictates otherwise. As used in this specification and the appended claims, the term “or” is generally employed to include “and/or, ” unless the content clearly dictates otherwise.

The following detailed description should be read with reference to the drawings, in which similar elements in different drawings are identified with the same reference numbers. The drawings, which are not necessarily to scale, depict illustrative embodiments and are not intended to limit the scope of the disclosure.

FIG. 1 illustrates an exemplary environment 100 where various embodiments of the present disclosure may function. As shown, the environment 100 primarily includes a buyer 102A or a viewer 102A, having an associated first computing device 104A comprising a behavior prediction system 106A, a seller 102B having an associated second computing device 104B having a behavior prediction system 106B, a server 108, and a network 110. The buyer 102A may be any person interested in buying a product/service displayed in a virtual 3D display of a place. The seller 102B can be any person selling or displaying product/service in the place. The buyer 102A may have to register with the behavior prediction system 106A by entering one or more personal details such as a name, an age, a location, a sex, and so forth on an interface of the computing device 104A. The buyer can see a virtual 3D display of the place on the computing device 104A by using the behavior prediction system 106A. Similarly, the seller 102B may register with the behavior prediction system 106B by entering one or more personal details such as a name, an age, a location, a sex, and so forth on an interface of the computing device 104B. The seller 102B may also view a virtual 3D view of the place and may also see how many buyers are showing interest or visiting the place. The buyer 102A and the seller 102B may have authorized login credentials for accessing a place such as, but not limited to, an exhibition or a virtual view of a location by using the behavior prediction system 106A-106B respectively and at least one of an augmented reality device/system or/and a virtual reality device/system. In an exemplary scenario, the behavior prediction system 106A may allow the buyer 102A to view an exhibition on the computing device 104A by entering valid login credentials from anywhere and at anytime. Further, the buyer 102A may not be required to physically visit the exhibition for viewing it. The buyer 102A may be presented with a three-dimensional (3D) virtual display including a virtual view of the exhibition/place by the behavior prediction system 106A such that the buyer 102A may feel as being part of the exhibition/place and virtually may feel the environment of the exhibition or the place. The examples of the exhibition may include a painting exhibition, a museum exhibition, and so forth. Further, an exhibition may be a display of products or services in an indoor area such as a hall, or in an outdoor area such as a ground.

In some embodiments, the behavior prediction system 106A-106B may be an application installed on the computing device 104A-104B respectively. In alternative embodiments, the buyer 102A may access the behavior prediction system 106A via a website URL on a web browser such as, but not limited to, Google Chrome, Internet Explorer, and so forth on the computing device 104A. In some embodiments, the behavior prediction system 106A-106B may be a single device or combination or multiple device or modules or systems capable of analyzing data generated during such as, a session of the buyer 102A while viewing the 3D virtual view of the place/exhibition. In some embodiments, the data is analyzed in real-time, and in alternate embodiments, the data is analyzed in non-real time. Further, the behavior prediction system 106A-106B may be software, hardware, firmware, and combination of these

The behavior prediction system 106A-106B is configured to present a virtual 3D display of the place to the buyer 102A and the seller 102B, respectively, such that the buyer 102A feels as being part of the virtual 3D display. The virtual 3D display comprises a plurality of scanned images. In some embodiments, the virtual 3D display is presented to the buyer 102A via at least one of a web based system, an augmented reality device and a virtual reality device.

The behavior prediction system 106A is further configured to sense a movement of the buyer 102A within the virtual 3D display and one or more gestures of the buyer 102A. Further, the behavior prediction system 106B on the second computing device 104B of the seller 102B is configured to capture at least one of a movement of the buyer 102A, one or more gestures of the buyer 102A while viewing of a virtual 3D display of a place, current preference of the buyer 102A, a number of products viewed by the buyer 102A, and a virtual path followed by the buyer 102A within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place.

Further, the behavior prediction system 106A is configured to receive a query from the buyer 102A about a product/service, wherein the query comprises at least one of a text message, an audio message, and a video message. The query and the sensed data may be sent to the prediction system 106B of the seller 102B. In some embodiments, the behavior prediction system 106A is configured to encrypt the query and data, and sends the encrypted query/data to the seller 102B of the product/service. In some embodiments, the query/data is sent to the seller 102B directly.

The behavior prediction system 106B is configured to analyze received and the captured movement of the

buyer

102A, 102A the one or more gestures of the buyer 102A while viewing of a virtual 3D display of a place, current preference of the buyer 102A, the number of products viewed by the buyer 102A, and the virtual path followed by the buyer 102A within the place. The behavior prediction system 106B is configured to predict the behavior of the buyer 102A within the virtual 3D display of the place based on the analysis. The behavior may be predicted in real-time. In some embodiments, the behavior prediction system 106A-106B may monitor one or more activities of the buyer 102A in real-time.

The behavior prediction system 106A is also configured to receive a response from the behavior prediction system 106B of the seller 102B. The response may be an encrypted response.

In some embodiments, the behavior prediction system 106A is further configured to authorize an access of the behavior prediction system to the buyer 102A based on a valid login credential for viewing the virtual 3D display of the place. Similarly, the behavior prediction system 106B is further configured to authorize an access of the behavior prediction system to the buyer 102A based on a valid login credential for viewing the virtual 3D display of the place. In further embodiments, the behavior prediction system 106A-106B is configured to store and maintain users’login credential information, history of the buyer 102A, interest of the buyer 102A, captured data, sensed movement data, details about one or more products/services, information of the plurality of exhibition/place, virtual 3D display, the plurality of scanned images, one or more activities of the buyer 102A while viewing the virtual 3D display. In some embodiments, the database is located on a remote device comprising the server 108.

The 3D scanned displays, scanned images, login credentials of the buyer 102A may be saved or stored either locally on the computing device 104A or on a database or storage device of the server 108. The server 108 may be a remotely located computation and storage device. In some embodiments, the data comprising users’login credential information, information of the plurality of exhibition, virtual 3D display, the plurality of scanned images, one or more activities of the buyer while viewing the virtual 3D display. The one or more activities of the buyer comprises a time spent at a particular position by the user, an area of the 3D display of the place viewed by the user, and so forth.

FIG. 2 illustrates a block diagram depicting various system elements of an exemplary behavior prediction system 202, in accordance with various embodiments of the present disclosure. As shown, the behavior prediction system 202 comprises an a transceiver 204, a display managing module 206, one or more sensors 208, a database 210, data capturing module 212, an analysis module 214, and a prediction module 216.

In some embodiments, a user, such as the seller 102B of FIG. 1, accesses the behavior prediction system 202 via a web browser on a computing device such as, a smart phone. The buyer 102A may view a virtual view of a place such as, an exhibition in real-time when the exhibition is actually happening. In some embodiments, the buyer 102A may view the exhibition at a later time may be after the exhibition has finished. The buyer 102A may view the place/exhibition anytime and from anywhere by using a smart phone comprising the behavior prediction system 202. In some embodiments, the buyer 102A may access the behavior prediction system 202 via a web browser application on the computing device.

The transceiver 204 is configured to receive or send data to and from the buyer 102A. In some embodiments, the transceiver 204 is configured to receive a query from the buyer 102A. The query and data may be encrypted. The seller 102B may enter a response at the behavior prediction system 202. The transceiver 204 is further configured to send the response to the behavior prediction system 106A. In some embodiments, the response is an encrypted response.

The display managing module 206 is configured to present the virtual 3D display of the place to the seller 102B such that the seller 102B feels as being part of the virtual 3D display. The virtual 3D display comprises a plurality of scanned images. In some embodiments, the display managing module 206 is configured to create the virtual 3D display based on the plurality of scanned images in real-time or non-real time. The virtual 3D display may be scanned model of the exhibition/place. In some embodiments, the virtual 3D display is presented to the seller 102B via at least one of a web based system, an augmented reality device and a virtual reality device. Further, the seller 102B may be able to view the virtual 3D display by using at least one of an augmented reality device or a virtual reality device.

The sensors 208 may be configured to sense a movement and one or more gestures of the buyer 102A or the seller 102B within the virtual 3D display.

The display managing module 206 is further configured to present the response to the buyer 102A in the virtual 3D display of the place. Further, the communication via the query and the response happens in real-time.

The data capture module 212 configured to capture at least one of a movement of the buyer 102A, one or more gestures of the buyer 102A while viewing of a virtual 3D display of a place, current preference of the buyer 102A, a number of products viewed by the buyer 102A, and a virtual path followed by the buyer 102A within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place.

The analysis module 214 configured to analyze captured movement of the buyer 102A, the one or more gestures of the buyer 102A while viewing of a virtual 3D display of a place, current preference of the buyer 102A, the number of products viewed by the buyer 102A, and the virtual path followed by the buyer 102A within the place.

The prediction module 216 configured to predict the behavior of the buyer 102A within the virtual 3D display of the place based on the analysis.

The database 210 is configured to store and maintain store and maintain users’login credential information, history of the user, interest of the user, behavior, captured data, seller and buyer preferences, encrypted queries and responses, details about one or more products/services, information of the plurality of exhibition/place, virtual 3D display, the plurality of scanned images, one or more activities of the buyer while viewing the virtual 3D display. The database 210 may be located on a remote device comprising a server.

FIG. 3 illustrates a flowchart of a method 300 for enabling a communication between a buyer and a seller in a virtual 3D display, in accordance with an embodiment of the present disclosure.

A virtual 3D view of a place is presented to the buyer 102A (or the seller 102B) such that the buyer 102A feels as being a part of the place. The place may be an exhibition. In some embodiments, the display managing module 206 presents the virtual 3D view of the place to the buyer 102A. In some embodiments, the buyer 102A views the display by using at least one of a web-based system, an augmented reality (AR) system, and a virtual reality (VR) system.

Then at step 302, the data capture module 212 captures the data comprising at least one of a movement of the buyer 102A, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer 102A, a number of products viewed by the buyer 102A, and a virtual path followed by the buyer within the place.

At step 304, the analysis module 214 of the behavior prediction system 202 on the second computing device 104B of the seller 102B analyzes the captured data. Thereafter, at step 306, the prediction module 216 predicts the behavior of the buyer 102A within the virtual 3D display of the place based on the analysis. The prediction module 216 may use suitable artificial intelligence techniques for predicting the behavior.

Embodiments of the disclosure are also described above with reference to flowchart illustrations and/or block diagrams of methods and systems. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the acts specified in the flowchart and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the acts specified in the flowchart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operations to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the acts specified in the flowchart and/or block diagram block or blocks.

In addition, methods and functions described herein are not limited to any particular sequence, and the acts or blocks relating thereto can be performed in other sequences that are appropriate. For example, described acts or blocks may be performed in an order other than that specifically disclosed, or multiple acts or blocks may be combined in a single act or block.

While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements.

Claims

A system for predicting a behavior of a buyer in a virtual three-dimensional (3D) display, the system comprising:

a data capture module configured to capture data comprising at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

an analysis module configured to analyze the captured data; and

a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis.
The system of claim 1, wherein the behavior is predicted in real-time.
A behavior prediction system comprising:

a data capture module configured to capture at least one of a movement of a buyer of a product/service displayed in a place, one or more gestures of the buyer while viewing of a virtual 3D display of the place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

an analysis module configured to analyze the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place in real-time; and

a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis in real-time.
A system for enabling a seller of a product/service to predict a behavior of a buyer viewing a virtual three-dimensional (3D) display, the system comprising:

a data capture module configured to capture at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

an analysis module configured to analyze captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and

a prediction module configured to predict the behavior of the buyer within the virtual 3D display of the place based on the analysis.
A method for predicting a behavior of a buyer in a virtual three-dimensional (3D) display, the system comprising:

capturing at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and

predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis.
The method of claim 1, wherein the behavior is predicted in real-time.
A method for behavior prediction comprising:

capturing at least one of a movement of a buyer of a product/service displayed in a place, one or more gestures of the buyer while viewing of a virtual 3D display of the place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place in real-time; and

predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis in real-time.
A method for enabling a seller of a product/service to predict a behavior of a buyer viewing a virtual three-dimensional (3D) display, the system comprising:

capturing data comprising at least one of a movement of the buyer, one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, a number of products viewed by the buyer, and a virtual path followed by the buyer within the place, wherein the virtual 3D display comprising a plurality of scanned images of the place;

analyzing the captured movement of the buyer, the one or more gestures of the buyer while viewing of a virtual 3D display of a place, current preference of the buyer, the number of products viewed by the buyer, and the virtual path followed by the buyer within the place; and

predicting the behavior of the buyer within the virtual 3D display of the place based on the analysis.
The method of claim 8 further comprising identifying one or more patterns of buyer behavior while viewing the virtual 3D display.