WO2014112407A1

WO2014112407A1 - Information processing system, information processing method, and program

Info

Publication number: WO2014112407A1
Application number: PCT/JP2014/050080
Authority: WO
Inventors: 有紀江海老山; 小西　勇介
Original assignee: 日本電気株式会社
Priority date: 2013-01-16
Filing date: 2014-01-07
Publication date: 2014-07-24

Abstract

[Program] To provide an information processing system, an information processing method, and a program, whereby it is possible to suitably detect a standstill of a moving body. [Solution] An information processing system (100) comprises: an input unit (110) which receives input of information relating to a location of a moving body in a region to be examined at each time point; and a score computation unit (130) which computes a score which denotes a degree of standstill relating to the region to be examined, according to a standstill time wherein each mobile body in the region to be examined stands still which is estimated on the basis of the location of each moving body at each time point.

Description

Information processing system, information processing method, and program

Some aspects according to the present invention relate to an information processing system, an information processing method, and a program.

In recent years, it has been considered to analyze human behavior based on video taken for a long time with a camera. For example, Patent Document 1 discloses detecting a staying location by using a video taken by a fixed camera such as a surveillance camera and quantifying the degree of human stillness, staying, gathering, etc. in an area of the shooting range. Yes. In the method described in Patent Document 1, scoring is performed on each block by dividing the region corresponding to the shooting range into a plurality of blocks and plotting the trajectory for each person. As a result, the block whose score is equal to or greater than the threshold is extracted as the staying location.

JP 2011-245945 A

However, in the method described in Patent Document 1, since the score is simply calculated based on the flow line of the person, for example, in the case of a terminal station, a lot of people are just moving without staying anywhere. Even if it exists, a score will become high and may be determined as a stay as a result.

Some aspects of the present invention have been made in view of the above-described problems, and one of the objects is to provide an information processing system, an information processing method, and a program that can suitably detect staying of a moving object. To do.

An information processing system according to the present invention includes: an input unit that receives input of information relating to the position of a moving body at each time in the target area; and the target area estimated based on the position of each moving body at each time. Calculating means for calculating a score indicating the degree of staying in the target area according to the staying time in which the moving body stays.

The image processing method according to the present invention includes a step of receiving information related to a position of a moving body at each time in the target area, and a movement to each target area estimated based on the position of each moving body at each time. The information processing system performs a step of calculating a score indicating a staying degree related to the target region according to a staying time in which the body stays.

The program according to the present invention includes a process for receiving input of information relating to the position of a moving body at each time in the target area, and each moving body in the target area estimated based on the position of each moving body at each time. In accordance with the staying time, the computer is caused to execute a process of calculating a score indicating the degree of staying related to the target area.

In the present invention, “part”, “means”, “apparatus”, and “system” do not simply mean physical means, but “part”, “means”, “apparatus”, “system”. This includes the case where the functions possessed by "are realized by software. Further, even if the functions of one “unit”, “means”, “apparatus”, and “system” are realized by two or more physical means or devices, two or more “parts” or “means”, The functions of “device” and “system” may be realized by a single physical means or device.

According to the present invention, it is possible to provide an information processing system, an information processing method, and a program that can suitably detect staying of a moving object.

It is a figure for demonstrating the outline | summary of the information processing system which concerns on 1st Embodiment. It is a functional block diagram which shows schematic structure of the information processing system which concerns on 1st Embodiment. It is a figure which shows the specific example of movement information. It is a figure for demonstrating the specific example of a process of a motion discrimination | determination part. It is a figure for demonstrating the specific example of a process of a motion discrimination | determination part. It is a figure for demonstrating the specific example of a process of a residence score calculation part. It is a figure for demonstrating the specific example of a process of a residence score calculation part. It is a figure for demonstrating the specific example of a process of a staying number calculation part. It is a flowchart which shows the flow of a process of the information processing system shown in FIG. It is a block diagram which shows the structure of the hardware which can mount the information processing system shown in FIG. It is a functional block diagram which shows schematic structure of the information processing system which concerns on 2nd Embodiment.

Embodiments of the present invention will be described below. In the following description and the description of the drawings to be referred to, the same or similar components are denoted by the same or similar reference numerals.

(1 First Embodiment)
1 to 10 are diagrams for explaining the first embodiment. Hereinafter, the present embodiment will be described according to the following flow with reference to these drawings. First, the outline of the system according to the present embodiment is described in “1.1”, and then the functional configuration of the system is described in “1.2” while showing specific examples of processing relating to each function. “1.3” describes the flow of processing, and “1.4” shows a specific example of a hardware configuration capable of realizing this system. Finally, the effects and the like according to the present embodiment will be described after “1.5”.

(1.1 Overview)
An outline of processing of the information processing system according to the present embodiment will be described with reference to FIG.

The information processing system according to the present embodiment is a system for determining whether or not a moving object is staying (stopped) in the stay determination area A1. As a specific example of the moving body, not only a person (human) but also a car, a truck, a bicycle, a motorcycle, and the like can be considered. In the following description, it is assumed that a person is staying. In addition, “person” in the following description refers to a person detected by the system unless there is a special description, and does not necessarily match one-to-one with an actual person. More specifically, for example, even if one person is actually moving, if each person detected at each timing cannot be detected by the system as being the same, The number will be multiple.

In the example of FIG. 1, only the stay determination area A1 is the target of stay determination in the whole, but the present invention is not limited to this, and a plurality of areas can be the target of stay determination. The region to be subject to stay determination may be determined in advance, or the information processing system may accept input of settings by the user as needed.

In the specific example of FIG. 1, the person P1 and the person P2 stay in the stay determination area A1 from time t0 to time t1, but the person P3 passes through the stay determination area A1 from time t0 to time t1. . In such a case, since the person P3 does not stay (not stay) in the stay determination area A1, the number of staying persons in the stay determination area A1 during the time period from time t0 to t1 can be determined to be two. it can.

Thereafter, from time t1 to time t2, the person P1 still remains in the stay determination area A1, but the person P2 has moved out of the stay determination area A1. Therefore, in such a case, it is possible to determine that the number of people staying in the stay determination area A1 from time t1 to time t2 is one person.

As described above, the information processing system according to the present embodiment does not consider the person who just passes through the stay determination area A1, and determines the stay degree based only on the person who stays purely in the stay determination area A1. Scoring (calculation of a score for determining the staying degree) is performed. Alternatively, a person who only passes through the stay determination area A1 performs scoring for stay determination with a lower score than the staying person.

According to such an information processing system, it is possible to detect a place where a large number of persons hang out without passing through, and therefore it is possible to accurately detect an area that should be noted in terms of security. Moreover, if it is used for various commercial facilities such as supermarkets and convenience stores, it becomes possible to determine the staying time and number of customers of each purchase shelf, so that it can be used for marketing. In addition, when used in, for example, a factory or a warehouse, the visualization of the work time for each area can detect chats between workers and can be used for verification of work efficiency.

As a method for acquiring movement information of the persons P1, P2, and P3 in the stay determination area A1, in the example of FIG. 1, the video camera C1 captures an area including the stay determination area A1, and then analyzes the captured video. Thus, a method of detecting the positions of the persons P1, P2, and P3 at each time is adopted. However, the method of acquiring the movement information of the person (moving body) is not limited to this, and any apparatus that can detect the position information of the person (moving body) and specify the detection time in the stay determination area A1 may be used. . Further, it is not necessary to detect a unique ID (identifier) for identifying each person (moving body). For example, a moving body using a camera, a floor pressure sensor, a laser range finder, a human sensor, or a radar that uses a sensor installed in a tracking environment and does not require the person (moving body) to hold the sensor. It can be realized by a tracking system. Alternatively, the mobile body itself needs to hold a device for position acquisition, but under the condition that a unique ID cannot be acquired from the device, a wireless communication device such as GPS (Global Positioning System) or ultrasonic waves You may implement | achieve by the mobile body tracking system etc. which used the receiver. In the following description, it is assumed that person movement information (position information at each time) is acquired based on an image captured by the video camera C1.

The movement information can be used even when there are a large number of persons in the stay determination area A1 and tracking is interrupted due to the overlapping of persons, or when a moving body other than a person is erroneously detected as a person. it can.

(1.2 System functional configuration)
Hereinafter, the system configuration of the information processing system 100 according to the present embodiment will be described with reference to FIG. FIG. 2 is a functional block diagram showing a functional configuration of the information processing system 100.

As shown in FIG. 2, the information processing system 100 roughly includes an input unit 110, a score calculation unit 130, and an output unit 140. Hereinafter, these configurations will be described in order.

(1.2.1 Input unit 110)
The input unit 110 receives input of movement information of each person. This information can be, for example, position information of a person at each time obtained by analyzing a video photographed by a video camera C1 or the like (possibly a plurality of video cameras C1). More specifically, for example, it is possible to obtain movement information for each person extracted as an object by comparing the feature amount of a person photographed by the video camera C1 and time-series images (frames).

There are various ways to input movement information. For example, movement information may be input from the video camera C1 as needed in real time, or movement information may be received by reading from a storage medium (not shown).

FIG. 3 shows an example of the movement information input to the input unit 110. In the example of FIG. 3, information on an ID assigned to each person (hereinafter also referred to as a mobile object ID) is associated with the time when each person is detected and its position (coordinates). Here, the movement information ID is identification information assigned to determine that the position information is related to the same moving body with respect to the position information of the moving body (for example, a person) that has been successfully detected continuously. That is, the position information group (position coordinate group) to which the same ID is assigned represents the locus of the same moving object. However, if the position detection of the moving body fails at a certain time, the trajectory of the moving body that has been detected until then is interrupted. For this reason, if the position detection of the moving object succeeds again after the position detection of the moving object fails, a new ID is assigned to the moving object.

(1.2.2 Score Calculation Unit 130)
The score calculation unit 130 calculates a residence score indicating the degree of residence in each time zone of the residence determination region A1 based on the flow line of the person (moving body detected as the same person) in each time zone. A time zone in which the stay score is high indicates that there are many staying people in the stay determination area A1. The score calculation unit 130 includes a motion determination unit 131, a stay score calculation unit 133, a staying number calculation unit 135, and stay determination area information 137.

(1.2.2.1 Motion discriminating unit 131)
The movement determination unit 131 specifies a person (flow line) that can be determined to be moving by determining the movement of each person in the stay determination area A1. Thereby, it becomes possible to calculate the staying score by excluding the flow line of the person who can be determined to be moving. Several methods for determining the movement of a person can be considered. Here, a motion line-based motion determination method and an image-based motion determination method will be described with reference to FIGS. 4 and 5.

The movement determination method based on the flow line is a technique for separating a moving person and a staying person by paying attention to the flow line of each person. A specific example will be described with reference to FIG.

In the example of FIG. 4, the flow line related to the person P4 in the target time zone for stay determination has a start point entering the stay determination area A1 and an end point exiting from the stay determination area A1. Accordingly, it can be determined that the person P4 has passed through the stay determination area A1 during this time period. Therefore, a person having a flow line having a start point entering the stay determination area A1 and an end point exiting from the stay determination area A1 can be determined to be moving without staying, and thus excluded from the stay score calculation. can do.

Further, in the example of FIG. 4, the moving speed of the person P5 in the target time zone for the stay determination is faster than the threshold value. Such a person P5 having a high moving speed can be considered not staying and can be excluded from the calculation of the staying score. The moving speed can be calculated by dividing the distance between the positions of the moving body at each time by the time required for the movement.

Subsequently, an image-based motion determination method will be described. In the image-based motion determination method, for example, using an optical flow, a human flow generation region in which a plurality of persons advance in the same direction at approximately the same speed is specified as shown in FIG. Since it can be considered that the person in the person flow generation area is moving without staying, it can be excluded from the calculation of the staying score.

Note that the motion discriminating unit 131 may use only one or both of the motion line-based motion determination method and the image-based motion determination method.

(1.2.2.2 Residence score calculation unit 133)
The stay score calculation unit 133 receives an input of a flow line related to the moving body determined to be staying by the motion determination unit 131, and calculates a stay score of the target time zone related to the stay determination region A1. There are several methods for calculating the stay score. Here, the stay score is calculated according to the sum of the flow rate detection time rate and the method of calculating the stay score based on the number of flow lines detected continuously over a certain time. A specific example of the calculation method will be described with reference to FIGS.

FIG. 6 is a diagram for explaining a method of calculating a residence score based on the number of flow lines detected continuously for a certain time or more. In the example of FIG. 6, it is assumed that four persons A to D are in the stay determination area A1 during times t0 to t1, which are target times for stay determination. Among these, the person A is 70% of the time period, the person B is 30% of the time, the person C is 20% of the time, and the person D is 80% of the time of the time in the stay determination area A1. It is assumed that a flow line has been detected. In such a case, in the method of calculating the stay score based on the number of flow lines detected continuously for a certain time or more, the person A and the person who are considered to have been in the stay determination area A1 in the target time zone for a threshold time of 50% or more D can be regarded as a staying person, and a staying score can be 2 (2 persons). Note that the threshold value may be determined in advance, or the information processing system 100 may accept input of settings by the user as needed.

Also, it is desirable that the target time length of the stay determination is determined by the size of the stay determination area A1 and the moving speed of the person who is the tracking target. That is, it is desirable to set a time longer than the time required to pass through the stay determination region A1 at the assumed moving speed of the moving body as the target time length for stay determination. The information processing system 100 may accept input of setting of the target time length from time to time by the user.

Subsequently, a method for calculating the staying score according to the sum of the flow line detection time rates will be described with reference to FIG. FIG. 7 is a diagram for explaining this method. In the example of FIG. 7, the time for the persons A to D to stay in the stay determination area A1 is the same as in the case of FIG. However, in this method, a residence score is calculated in proportion to each residence time rate. Since the stay time of each of the persons A to D is 70%, 30%, 20%, and 80%, the total of 2 (0.7 + 0.3 + 0.2 + 0.8) is added to the number of people staying in the time period. It can be set as the residence score equivalent to.

By calculating the stay score for each time period subject to stay determination using the above method, even if there is a break in the flow line of the moving body (here, a person), the tracking target is based on the continuous detection time length of the flow line. It is possible to score the degree to which a certain mobile object is stationary.

(1.2.2.3 Residence number calculation unit 135)
The staying number calculation unit 135 is for correcting the staying score calculated by the staying score calculation unit 133 and corresponding to the number of staying people in the target time zone.

For example, when extracting a person from video captured by the video camera C1, there is a possibility that the person is erroneously extracted if each person overlaps, is hidden behind the object, or has a dim position. Therefore, the staying number calculation unit 135 has a function for correcting such a person extraction error.

First, as a first correction method, a method for estimating the number of staying persons using a stay determination result for a certain period of time in the past or the future and a flow line detected around (in the vicinity of) the stay determination area can be considered. FIG. 8 is a diagram for explaining a specific example of the method. In the example of FIG. 8, in the video at time t−1 and time t + 1, since the persons P9 and P10 can be correctly extracted as separate persons, the number of detected persons can be two. On the other hand, in the video at time t, since the persons P9 and P10 overlap, the number of detected persons is one.

However, if no new person coming out of the video is detected between time t-1 and time t, it is assumed that there are two people in the video area even at time t. Can do. Also, even when no new person entering the video is detected between time t and time t + 1, it is possible to estimate that there are two people in the video area at time t. It is.

As described above, the staying number calculation unit 135 can estimate the staying number of persons in the time zone that is the reference target of the staying score by analyzing the transition of the staying number of persons over a plurality of time periods and the presence or absence of the flow line. . This estimation can be performed only in the time zone (past) before the target time zone or only in the time zone (future) after the target time zone. However, if both are used, estimation with higher accuracy can be performed.

In addition, although it demonstrated on the assumption that a flow line was detected here, it is not restricted to this. For example, since it is not always possible to properly detect the flow line due to circumstances such as being unable to detect the same person, whether or not there is a person detected in the vicinity of the area when the number of people detected in the stay determination area changes. Can also estimate the number of people. Explaining in the above example, the number of detected people has changed from two to one from time t-1 to time t, but if no person can be detected near the stay determination area at time t, It can be estimated that there are two persons in the determination area. Similarly, the number of detected people has changed from one to two from time t to time t + 1, but if no person near the stay determination area can be detected at time t, two people at time t can be detected. It can be estimated that there was a person.

In addition, it is conceivable to adjust the staying score according to the position. As described above, for example, when extracting a person from a video, it may be difficult to extract a person depending on the position. Therefore, for example, the retention score is corrected by multiplying a low coefficient for the number of flow lines (number of people) in areas where flow lines are easy to detect, and a high coefficient for the number of flow lines (number of people) in areas where flow lines are difficult to detect. can do.
In particular, when a person is detected by image processing, a recognition error is likely to occur. Therefore, by performing such correction, it is possible to calculate a suitable stay score.

Note that the staying number calculation unit 135 may use only one of the stay score adjustment based on the flow line analysis in a plurality of time zones and the stay score adjustment according to the coefficient based on the position, or both. It is also possible.

(1.2.2.4 Residence determination area information 137)
The stay determination area information 137 is information related to the coordinates of the stay determination area A1. In particular, when the stay determination region A1 is a part of the region of the flow line specified based on the movement information input from the input unit 110, the motion determination unit 131, the stay score calculation unit 133, and the stay The number calculation unit 135 analyzes the information in the stay determination area A1 while referring to the stay determination area information 137.
The stay determination area may be defined in any shape such as a polygon or a circle. If the position coordinates of the stay determination area are polygons, the vertex coordinates are input, and the coordinates and radius of the center point of the circle are entered. You can enter. Further, when setting a plurality of stay determination areas, they may be set so as to overlap each other, or may be installed so as not to overlap each other.

(1.2.3 Output section)
The output unit 140 outputs the residence score calculated by the score calculation unit 130 and corresponding to the number of people staying in the stay determination region A1 in the target time zone, in association with the coordinates (position) and time of the stay determination region A1. At this time, it is also possible to output a stay score relating to a plurality of monitoring areas over a plurality of time zones. If implemented in this way, it is possible to identify the time transition of the residence score, the difference for each region, and the like.

There are a plurality of methods for outputting the retention score. For example, the stay score can be simply output as a numerical value, and the stay score is output by causing the display device to display a map screen in which the shade of the area on the map changes according to the stay score. It is also possible.
Alternatively, when there is a region where the retention score exceeds a predetermined threshold, the display device may notify the occurrence of the retention by a message such as “Residence has occurred in front of convenience store A”, for example. .

(1.3 Process flow)
Hereinafter, the processing flow of the information processing system 100 will be described with reference to FIG. FIG. 9 is a flowchart showing a processing flow of the information processing system 100 according to the present embodiment.

Each processing step to be described later can be executed in any order or in parallel as long as there is no contradiction in processing contents, and other steps can be added between the processing steps. good. Further, a step described as a single step for convenience can be executed by being divided into a plurality of steps, and a step described as being divided into a plurality of steps for convenience can be executed as one step.

First, the input unit 110 receives the movement information illustrated in FIG. 3 (S901). As described above, a plurality of movement information input methods are conceivable. In addition to the case where the movement information recorded in the storage medium is read in addition to the case where the movement information is input in real time by analyzing the video captured by the video camera C1 or the like. It is done.

The motion discriminating unit 131 discriminates whether or not each person is moving by discriminating the motion of each person based on the flow line specified based on the movement information input from the input unit 110 ( S905). As described above, as described above, when the movement is determined based on the flow line, it is determined whether the movement line crosses the stay determination area A1, and the speed of each moving body exceeds the threshold value based on the flow line. It is conceivable to make a determination by identifying whether or not it is. When discriminating on the basis of an image, it is possible to first identify a human flow generation region and then determine that a flow line (person) on the human flow generation region is moving.

The staying score calculation unit 133 calculates a staying score corresponding to the number of staying persons in the target time zone based on the flow line excluding the flow line (person) determined as the movement determination unit 131 moving (S907). ). As a score calculation method, for example, as described with reference to FIGS. 6 and 7, the score is calculated according to the number of flow lines detected in the stay determination region A1 for a certain period of time, or for each moving object. It may be calculated according to the detection time length.

After the calculation by the staying score calculation unit 133, the staying number calculation unit 135 corrects the staying score (S909). As the correction method, as described above, it is conceivable to perform correction according to the position of the flow line (person) or correction based on the flow line analysis of a person including past and / or future time zones.

In addition, the process of S905 thru | or S909 processes sequentially, shifting a time window for every time slot | zone of residence determination object.

After correcting the stay score in this way, the output unit 140 outputs stay information (S911). The stay information includes a stay score, a time zone, and position information of the target stay determination area A1.

(1.4 Hardware configuration)
Hereinafter, an example of a hardware configuration when the information processing system 100 described above is realized by a computer will be described with reference to FIG. The information processing system 100 can also be realized by a plurality of information processing apparatuses.

As shown in FIG. 10, the information processing system 100 includes a processor 1001, a memory 1003, a storage device 1005, an input interface (I / F) 1007, a data I / F 1009, a communication I / F 1011, and a display device 1013.

The processor 1001 controls various processes in the information processing system 100 by executing a program stored in the memory 1003. For example, the processing related to the input unit 110, the score calculation unit 130, and the output unit 140 described in FIG. 2 can be realized as a program mainly operating on the processor 1001 after being temporarily stored in the memory 1003.

The memory 1003 is a storage medium such as a RAM (Random Access Memory). The memory 1003 temporarily stores a program code of a program executed by the processor 1001 and data necessary for executing the program. For example, in the storage area of the memory 1003, a stack area necessary for program execution is secured.

The storage device 1005 is a non-volatile storage medium such as a hard disk or flash memory. The storage device 1005 stores an operating system, various programs for realizing the input unit 110, the score calculation unit 130, and the output unit 140, various data such as the stay determination area information 137, and the like. Programs and data stored in the storage device 1005 are referred to by the processor 1001 by being loaded into the memory 1003 as necessary.

The input I / F 1007 is a device for receiving input from the user. Specific examples of the input I / F 1007 include a keyboard, a mouse, a touch panel, and various sensors. The input I / F 1007 may be connected to the information processing system 100 via an interface such as USB (Universal Serial Bus), for example.

The data I / F 1009 is a device for inputting data from outside the information processing system 100. Specific examples of the data I / F 1009 include a drive device for reading data stored in various storage media. The data I / F 1009 may be provided outside the information processing system 100. In that case, the data I / F 1009 is connected to the information processing system 100 via an interface such as a USB.

The communication I / F 1011 is a device for performing data communication with an external device of the information processing system 100, for example, a video camera C1 or the like by wire or wireless. The communication I / F 1011 may be provided outside the information processing system 100. In this case, the communication I / F 1011 is connected to the information processing system 100 via an interface such as a USB.

The display device 1013 is a device for displaying various information. Specific examples of the display device 1013 include a liquid crystal display and an organic EL (Electro-Luminescence) display. The display device 1013 may be provided outside the information processing system 100. In that case, the display device 1013 is connected to the information processing system 100 via, for example, a display cable.

(1.5 Effects according to this embodiment)
As described above, in the information processing system 100 according to the present embodiment, it is possible to suitably detect staying of a moving body such as a person. For this reason, for example, a flow line related to a moving body that can be determined to be moving by the movement determination unit 131 is excluded from the calculation of the staying score. In addition, since the stay score calculation unit 133 calculates the stay score based on the stay time, a person who stays only for a short time has no or little influence on the stay score. Further, since the staying number calculating unit 135 corrects the staying number, even when there is an error in the staying number identification, the correction is possible.

(2 Second Embodiment)
The second embodiment will be described below with reference to FIG. FIG. 11 is a block diagram illustrating a functional configuration of the information processing system 1100. As illustrated in FIG. 11, the information processing system 1100 includes an input unit 1110 and a calculation unit 1120.
The input unit 1110 receives input of information relating to the position of the moving body at each time in the target area for which the stay score is calculated.

The calculation unit 1120 calculates a score indicating the degree of stay in the target area according to the stay time in which each mobile body stays in the target area, which is estimated based on the position of each mobile body at each time.
By mounting in this way, according to the information processing system 1100 according to the present embodiment, it is possible to suitably detect staying of the moving body.

(3 Additional notes)
Note that the configurations of the above-described embodiments may be combined or some of the components may be replaced. The configuration of the present invention is not limited to the above-described embodiment, and various modifications may be made without departing from the scope of the present invention.

Note that part or all of the above-described embodiments can be described as in the following supplementary notes, but is not limited to the following. Moreover, the program of this invention should just be a program which makes a computer perform each operation | movement demonstrated in said each embodiment.

(Appendix 1)
According to the input means for receiving information related to the position of the moving body at each time in the target area, and the continuous detection time of each moving body in the target area estimated based on the position of each moving body at each time An information processing system comprising: a calculating unit that calculates a score indicating the degree of staying in the target area.

(Appendix 2)
The information processing system according to supplementary note 1, wherein the calculation unit calculates the score based on the number of moving objects whose continuous detection time of moving objects in the target region is equal to or greater than a threshold value.

(Appendix 3)
When the score calculated in the target area is changed with respect to time, the calculating unit is configured to determine whether or not there is a moving body detected in the vicinity of the target area at the changed time. The information processing system according to attachment 2, wherein the number of moving objects is estimated.

(Appendix 4)
The information processing system according to supplementary note 1, wherein the calculation unit calculates the score based on a total of continuous detection times of the moving objects in the target region.

(Appendix 5)
5. The information processing system according to claim 1, wherein the calculation unit calculates the score excluding a moving body that can be determined to have passed through the target region.

(Appendix 6)
The calculation means determines a human current area in the target area based on the position of each mobile object at each time, and according to the continuous detection time of each mobile object in the area of the target area excluding the human current area. The information processing system according to any one of supplementary notes 1 to 5, wherein the score is calculated.

(Appendix 7)
The calculation means includes a continuous detection time of the moving body in the first region of the target region, and a continuous detection time of the mobile body in the second region where the detection of the moving body is more difficult than the first region. The information processing system according to any one of appendices 1 to 6, wherein the score is calculated by multiplying each by a different coefficient.

(Appendix 8)
According to the step of receiving information related to the position of the moving body at each time in the target area, and the continuous detection time of each moving body in the target area estimated based on the position of each moving body at each time, An information processing method in which the information processing system performs a step of calculating a score indicating the degree of stay in the target area.

(Appendix 9)
The information processing method according to appendix 8, wherein the score is calculated based on the number of moving objects for which the continuous detection time of moving objects in the target region is equal to or greater than a threshold value.

(Appendix 10)
When a change with respect to time occurs in the score calculated in the target area, the number of moving bodies in the target area is calculated based on the presence or absence of the mobile body detected in the vicinity of the target area at the changed time. The information processing method according to appendix 9, which is estimated.

(Appendix 11)
The information processing method according to appendix 8, wherein the score is calculated based on a total of continuous detection times of the moving objects in the target region.

(Appendix 12)
The information processing method according to any one of appendices 8 to 11, wherein the score is calculated by removing a moving body that can be determined to have passed through the target region.

(Appendix 13)
Based on the position of each moving body at each time, a human current area in the target area is determined, and the score is calculated according to the continuous detection time of each moving body in the target area other than the human current area. The information processing method according to any one of supplementary notes 8 to 12.

(Appendix 14)
Different coefficients are used for the continuous detection time of the moving object in the first region of the target region and the continuous detection time of the moving object in the second region where detection of the moving object is more difficult than in the first region. 14. The information processing method according to any one of supplementary notes 8 to 13, wherein the score is calculated by multiplying.

(Appendix 15)
According to the process of receiving information related to the position of the moving body at each time in the target area, and the continuous detection time of each moving body in the target area, which is estimated based on the position of each moving body at each time, The program which makes a computer perform the process which calculates the score which shows the degree of stay concerning the said object area | region.

(Appendix 16)
The program according to appendix 15, wherein the score is calculated based on the number of moving objects for which the continuous detection time of moving objects in the target region is equal to or greater than a threshold value.

(Appendix 17)
When a change with respect to time occurs in the score calculated in the target area, the number of moving bodies in the target area is calculated based on the presence or absence of the mobile body detected in the vicinity of the target area at the changed time. The program according to appendix 16, which is estimated.

(Appendix 18)
The program according to claim 15, wherein the score is calculated based on a total of continuous detection times of the respective moving objects in the target region.

(Appendix 19)
The program according to any one of appendix 15 to appendix 18, wherein the score is calculated by removing a moving body that can be identified as having passed through the target region.

(Appendix 20)
Based on the position of each moving body at each time, a human current area in the target area is determined, and the score is calculated according to the continuous detection time of each moving body in the target area other than the human current area. The program according to any one of supplementary notes 15 to 19.

(Appendix 21)
The continuous detection time of each moving body in the first area of the target area is different from the continuous detection time of each moving body in the second area where it is more difficult to detect the moving body than the first area. The program according to any one of supplementary notes 15 to 20, wherein the score is calculated by multiplying by a coefficient.

(Appendix 22)
An information processing system comprising: an input unit that receives an input of a position of a moving body at each time in a target region; and a calculation unit that calculates a degree of staying in the target region based on the position of each moving body at each time .

(Appendix 23)
The information processing system performs a step of receiving an input of a position of each moving body at each time in the target region, and a step of calculating a staying degree related to the target region based on the position of each moving body at each time Information processing method.

(Appendix 24)
A program that causes a computer to execute a process of receiving an input of a position of a moving body at each time in a target area and a process of calculating a degree of stay related to the target area based on the position of each moving body at each time.

(Appendix 25)
Input means for receiving video input;
A display device that changes a display mode of the target area according to a residence time of the moving object in the target area of the video;
An information processing system comprising:

(Appendix 26)
Receiving video input,
Changing the display mode of the target area according to the residence time of the moving object in the target area of the video;
An information processing method in which the information processing system performs.

(Appendix 27)
Processing to receive video input,
A process of changing the display mode of the target area according to the residence time of the moving object in the target area of the video;
A program that causes a computer to execute.

This application claims priority based on Japanese Patent Application No. 2013-5505 filed on January 16, 2013, the entire disclosure of which is incorporated herein.

DESCRIPTION OF SYMBOLS 100 ... Information processing system, 110 ... Input part, 130 ... Score calculation part, 131 ... Motion discrimination | determination part, 133 ... Retention score calculation part, 135 ... Retention number calculation part, 137 ... Residence determination area information, 140 ... Output unit, 1001 ... Processor, 1003 ... Memory, 1005 ... Storage device, 1007 ... Input interface, 1009 ... Data interface, 1011 ..Communication interface, 1013 ... display device, 1100 ... information processing system, 1110 ... input unit, 1120 ... calculation unit

Claims

Input means for receiving input of information relating to the position of the moving body at each time in the target area;
Information comprising: a calculating means for calculating a score indicating the degree of stay in the target area according to the continuous detection time of each moving body in the target area, which is estimated based on the position of each moving body at each time Processing system.
The calculating means calculates the score based on the number of moving objects for which the continuous detection time of the moving object in the target region is equal to or greater than a threshold;
The information processing system according to claim 1.
When the score calculated in the target area is changed with respect to time, the calculating unit is configured to determine whether or not there is a moving body detected in the vicinity of the target area at the changed time. Estimate the number of moving objects,
The information processing system according to claim 2.
The calculating means calculates the score based on a total of continuous detection times of the moving objects in the target region;
The information processing system according to claim 1.
The information processing system according to any one of claims 1 to 4, wherein the calculation means calculates the score excluding a moving body that can be determined to have passed through the target region.
The calculation means determines a human current area in the target area based on the position of each mobile object at each time, and according to a continuous detection time of each mobile object in an area of the target area excluding the human current area. Calculating the score,
The information processing system according to any one of claims 1 to 5.
The calculating means includes a continuous detection time of each moving body in the first area of the target area, and a continuous detection of each moving body in the second area where it is more difficult to detect the moving body than the first area. Calculating the score by multiplying time by a different coefficient,
The information processing system according to any one of claims 1 to 6.
Receiving information related to the position of each mobile object at each time in the target area;
Calculating a score indicating the degree of stay in the target area according to the continuous detection time of each moving body in the target area, which is estimated based on the position of each mobile body at each time. Information processing method performed by
A process of receiving input of information relating to the position of the moving object at each time in the target area;
The computer executes a process of calculating a score indicating the degree of stay in the target area according to the continuous detection time of each moving body in the target area, which is estimated based on the position of each moving body at each time Program to make.
An input means for receiving an input of the position of the moving body at each time in the target area;
An information processing system comprising: a calculating unit that calculates a staying degree related to the target area based on the position of each moving body at each time.
Input means for receiving video input;
A display device that changes a display mode of the target area according to a residence time of the moving object in the target area of the video;
An information processing system comprising: