JP2017046023A - Mobile tracking device, mobile tracking method and mobile tracking program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To track a mobile of a tracking target indoors even in the case where the mobile of the tracking target cannot be detected in a captured image.SOLUTION: Based on at least either a field intensity of a radio wave from a radio terminal device moving with a mobile measured at each of a plurality of pieces of radio communication equipment disposed separately in a target area or a field intensity of a radio wave from each of the plurality of pieces of radio communication equipment measured at the radio terminal device, a moving route prediction part 42 estimates a current position of the mobile and predicts a moving route of the mobile. Based on imaging possible ranges of a plurality of imaging apparatuses disposed separately in the target area and the moving route predicted by the moving route prediction part 42, an imaging apparatus control part 43 selects an imaging apparatus which is caused to image the mobile moving along the moving route, from among the plurality of imaging apparatuses.SELECTED DRAWING: Figure 4

Description

  The present invention relates to a technique for tracking a moving object.

A technique in which a plurality of imaging devices cooperate to track a moving object is known.
A conventional tracking device has an image analysis device, detects an image to be tracked from within a captured image, shares position information of the imaging device and information about the movement of the tracking target in the image via a network, and The tracking target is tracked by issuing a tracking control command to the imaging apparatus in which the target object is expected to fall within the imaging range (for example, Patent Document 1).
There is also a technique for tracking a moving body in a video of an imaging device by combining the position information of the moving body transmitted from a mobile terminal device with image analysis information (for example, Patent Document 2).

Japanese Patent Laying-Open No. 2015-2553 JP 2002-290963 A

However, the tracking of the moving object by the conventional image analysis has a problem that the moving object cannot be detected due to the direction of the shielding object or the moving object, and the tracking becomes difficult.
In particular, in a crowded situation such as a commercial facility or a station, a person with a short height, such as a child, may be shielded by a person with a high height around him, and there is a possibility that the figure does not appear in the captured image. is there.
Further, the position information used in Patent Document 2 is assumed to be used outdoors, and there is a problem that it cannot be applied to an imaging apparatus installed indoors in a station premises, a commercial facility, or the like.

  The main object of the present invention is to solve the above-described problems. A configuration in which a tracking target moving body can be tracked indoors even when the tracking target moving body cannot be detected in a captured image. The main purpose is to obtain.

The mobile tracking device according to the present invention is:
The radio wave intensity of radio waves from a radio terminal device moving with a mobile object, measured by each of a plurality of radio communication devices arranged separately in a target area, or the radio waves measured by the radio terminal device Based on at least one of the radio field strengths of radio waves from each of the communication devices, a current path of the mobile body is estimated, and a travel path prediction unit that predicts a travel path of the mobile body;
From the plurality of imaging devices, based on the imageable range of each of the plurality of imaging devices arranged separately in the target area and the movement path predicted by the movement route prediction unit, An imaging device control unit that selects an imaging device that captures an image of the moving body moving along the movement path.

In the present invention, the current position of the moving body is estimated based on the radio wave intensity, the moving path of the moving body is predicted, and the imaging apparatus that captures the moving body is selected based on the predicted moving path.
Therefore, according to the present invention, the tracking target moving body can be tracked indoors even when the tracking target moving body cannot be detected in the captured image.

1 is a diagram illustrating a configuration example of a mobile terminal cooperation mobile body tracking system according to Embodiment 1. FIG. FIG. 3 is a diagram illustrating a functional configuration example of a mobile terminal device according to the first embodiment. 3 is a diagram illustrating an example of a functional configuration of a wireless communication device according to Embodiment 1. FIG. FIG. 3 is a diagram illustrating a functional configuration example of a mobile terminal cooperation device according to the first embodiment. FIG. 3 is a diagram illustrating a functional configuration example of the imaging apparatus according to Embodiment 1; The figure which shows the internal structural example of the movement route estimation part which concerns on Embodiment 1. FIG. FIG. 3 is a diagram illustrating an internal configuration example of an imaging apparatus control unit according to the first embodiment. FIG. 3 is a flowchart showing an operation example of the mobile terminal cooperation device according to the first embodiment. FIG. 3 is a sequence diagram illustrating an operation example of the mobile terminal cooperative mobile tracking system according to the first embodiment. FIG. 3 illustrates an arrangement example of a wireless communication device and an imaging device according to Embodiment 1; The figure which shows the structural example of the mobile terminal cooperation mobile body tracking system which concerns on Embodiment 2. FIG. FIG. 6 is a diagram illustrating a functional configuration example of a mobile terminal cooperation device according to a second embodiment. FIG. 4 is a diagram illustrating a functional configuration example of an image analysis device according to a second embodiment. FIG. 4 is a diagram illustrating an example of a functional configuration of an imaging apparatus according to Embodiment 2. FIG. 6 is a flowchart showing an operation example of the mobile terminal cooperation device according to the second embodiment. FIG. 10 is a sequence diagram showing an operation example of the mobile terminal cooperative mobile tracking system according to the second embodiment. The figure which shows the hardware structural example of the mobile terminal cooperation apparatus which concerns on Embodiment 1 and 2. FIG. FIG. 5 is a diagram showing an example of travel route history data according to the first embodiment. The figure which shows the example of the movement path | route log | history of the tracking object person which concerns on Embodiment 1. FIG.

Embodiment 1 FIG.
In the present embodiment, a mobile terminal cooperation mobile body tracking system that includes a mobile terminal apparatus that is a wireless communication terminal apparatus, a plurality of imaging apparatuses, and a plurality of wireless communication apparatuses and tracks a mobile body will be described.
In the present embodiment, the moving object is a person carrying the mobile terminal device.
Hereinafter, the person to be tracked who carries the mobile terminal device is referred to as a person to be tracked.
The mobile terminal cooperative mobile tracking system according to the present embodiment uses the radio field strength of a wireless communication device to perform a movement path prediction of a tracking target person having a mobile terminal device, and captures the predicted movement path of the tracking target person Provide control commands to possible imaging devices.

*** Explanation of configuration ***
The mobile terminal cooperation mobile body tracking system according to the present embodiment includes at least a mobile terminal device having a wireless communication function, a plurality of imaging devices having different fields of view, a plurality of wireless communication devices installed at different positions, a movement path prediction, and The mobile terminal cooperation apparatus which controls an imaging device consists of the structure connected via the network.
Wireless standards such as Wi-Fi, Bluetooth (registered trademark), and Bluetooth (registered trademark) Low Energy are used for communication between the mobile terminal device and the wireless communication device.
Note that the mobile terminal cooperation mobile body tracking system according to the present embodiment may be connected to the monitoring control device through the Internet.
In addition, the mobile terminal cooperative mobile tracking system according to the present embodiment may be connected to other devices (recording device, display device, mobile terminal device) through the Internet.
Hereinafter, the structure of the mobile terminal cooperation mobile body tracking system of this Embodiment is demonstrated using FIGS.

  FIG. 1 is a system configuration diagram of a mobile terminal cooperation mobile body tracking system 1 according to the present embodiment.

The mobile terminal cooperation mobile body tracking system 1 according to the present embodiment includes a mobile terminal device 2 and wireless communication devices 3 _{1 to} 3 _n (hereinafter may be collectively referred to as wireless communication device 3), a mobile terminal cooperation device 4, Imaging devices 5 _{1 to} 5 _n (hereinafter may be collectively referred to as imaging device 5) are provided.
The numbers of the wireless communication device 3 and the imaging device 5 are not limited to the example illustrated in FIG.

The mobile terminal device 2 moves with the tracking target person.
The mobile terminal device 2 has a wireless communication function.
The mobile terminal device 2 also has a function of measuring the radio field intensity of radio waves from the wireless communication devices 3 _{1 to} 3 _n .
The mobile terminal device 2 corresponds to an example of a wireless terminal device.
Details of the mobile terminal device 2 will be described later with reference to FIG.

The wireless communication devices 3 _{1 to} 3 _n are arranged to be separated from each other in a target area that is tracked by the mobile terminal cooperative mobile tracking system 1.
The wireless communication devices 3 _{1 to} 3 _n have a wireless communication function.
The wireless communication devices 3 _{1 to} 3 _n also have a function of measuring the radio field intensity of the radio wave from the mobile terminal device 2.
Details of the wireless communication devices 3 _{1 to} 3 _n will be described later with reference to FIG.

The mobile terminal cooperation device 4 estimates the current position of the tracking target person possessing the mobile terminal device 2, predicts the movement path of the tracking target person, and can capture the tracking target person moving along the predicted movement path. The device 5 is selected and the selected imaging device 5 is controlled.
The mobile terminal cooperation device 4 corresponds to an example of a mobile body tracking device.
Details of the mobile terminal cooperation device 4 will be described later with reference to FIG.

The imaging devices 5 _{1 to} 5 _n capture a person based on the control from the mobile terminal cooperation device 4.
Details of the imaging devices 5 _{1 to} 5 _n will be described later with reference to FIG.
The imaging devices 5 _{1 to} 5 _n are also referred to as cameras.

  Hereinafter, functional configurations of the mobile terminal device 2, the wireless communication device 3, the mobile terminal cooperation device 4, and the imaging device 5 will be described with reference to FIGS.

<Mobile terminal device>
The mobile terminal device 2 includes a user ID acquisition unit 21, a sensor information acquisition unit 22, and a wireless communication unit 23 (FIG. 2).
The mobile terminal device 2 has a unique user ID (Identifier) for each terminal, and acquires this from the user ID acquisition unit 21.
The user ID may be used by the mobile terminal cooperation apparatus 4 to refer to personal information, movement history, etc. of the person to be tracked.
The mobile terminal device 2 includes an acceleration sensor, a geomagnetic sensor, a gyro sensor, and the like, and the sensor information acquisition unit 22 acquires each sensor value.
The mobile terminal device 2 communicates with the wireless communication device 3 through the wireless communication unit 23.
The wireless communication unit 23 has functions of wireless transmission / reception and measurement of radio wave intensity.

<Wireless communication device>
The wireless communication device 3 includes a wireless communication unit 31, a data acquisition unit 32, and an internal communication unit 33 (FIG. 3).
The wireless communication unit 31 communicates with the mobile terminal device 2.
The data acquisition unit 32 acquires data transmitted from the mobile terminal device 2.
The internal communication unit 33 communicates with the mobile terminal cooperation device 4.

<Mobile terminal cooperation device>
The mobile terminal cooperation device 4 includes an internal communication unit 41, a movement route prediction unit 42, and an imaging device control unit 43 (FIG. 4).
The internal communication unit 41 communicates with the wireless communication device 3.
The movement route prediction unit 42 predicts the movement route of the tracking target person based on the data acquired from the mobile terminal device 2.
More specifically, the movement path prediction unit 42 is configured to measure the radio field intensity of the radio wave from the mobile terminal device 2 or the radio communication device measured by the mobile terminal device 2 measured by each of the radio communication devices 3 _{1 to} 3 _n. The current position of the person to be tracked is estimated based on at least one of the radio field intensities of the radio waves from 3 _{1 to} 3 _n .
Furthermore, the movement route prediction unit 42 predicts the movement route of the tracking target person from the estimated current position of the tracking target person.
The process performed by the movement route prediction unit 42 corresponds to a movement route prediction step.
The imaging device control unit 43 controls the imaging device 5 based on the predicted movement path.
More specifically, the imaging apparatus control unit 43, based on the imaging range of each of the imaging device 5 ₁ to 5 _n, the moving path predicted by the movement path prediction section 42, the imaging device 5 ₁ to 5 _n The imaging device 5 that captures the person to be tracked moving along the movement path is selected.
Further, the imaging device control unit 43 performs control for causing the tracking target person to be photographed with respect to the selected imaging device 5.
The process performed by the imaging device control unit 43 corresponds to an imaging device control step.
The imaging device 5 is connected to the mobile terminal cooperation device 4 using a network cable or a coaxial cable.

<Imaging device>
The imaging device 5 includes an internal communication unit 51, a PTZ (pan / tilt / zoom) control unit 52, and an image acquisition unit 53 (FIG. 5).
The internal communication unit 51 communicates with the mobile terminal cooperation device 4 via the communication network B.
The PTZ control unit 52 controls pan / tilt / zoom of the imaging device 5 based on an instruction from the mobile terminal cooperation device 4.

*** Explanation of operation ***
Next, the operation of the mobile terminal cooperative mobile body tracking system 1 according to the present embodiment will be described.

<Communication between mobile terminal device 2 and wireless communication device 3>
First, the radio communication unit 31 of the radio communication device 3 acquires the radio field intensity transmitted from the radio communication unit 23 of the mobile terminal device 2.
When performing this communication, it is also possible to acquire and transmit user sensor information and user ID from the sensor information acquisition unit 22 and the user ID acquisition unit 21 of the mobile terminal device 2.
In that case, the user ID and sensor information are acquired by the data acquisition unit 32 of the wireless communication device 3.
In the above wireless communication, the radio wave intensity of the radio wave emitted by the mobile terminal device 2 is measured by the radio communication device 3, but the radio wave intensity of the radio wave emitted by the radio communication device 3 is measured by the mobile terminal device 2 and measured. The result may be transmitted to the wireless communication device 3.
By these methods, the radio field intensity corresponding to the number of installed wireless communication devices 3 within the connectable range can be acquired from the mobile terminal device 2.

<Communication between the wireless communication device 3 and the mobile terminal cooperation device 4>
The wireless communication device 3 transmits data (radio wave intensity, user ID, various sensor information) acquired from the mobile terminal device 2 to the mobile terminal cooperation device 4 via the communication network 1 from the internal communication unit 33.
The mobile terminal cooperation device 4 acquires the above data from the internal communication unit 41.

<Operation of Mobile Terminal Cooperation Device 4>
Next, an operation example of the mobile terminal cooperation device 4 will be described with reference to FIGS.
FIG. 6 illustrates an internal configuration example of the movement route prediction unit 42.
FIG. 7 shows an internal configuration example of the imaging device control unit 43.
FIG. 8 shows an operation flow of the mobile terminal cooperation device 4.
Note that the operation flow of FIG. 8 shows an example of processing for realizing the first embodiment, and does not limit the implementation method.
In addition, the operation procedure of the mobile terminal cooperation device 4 described below corresponds to an example of a moving body tracking method and a moving body tracking program.

When the internal communication unit 41 receives data including the user ID and the radio wave intensity from the wireless communication device 3 (S11), when there is a mobile terminal device to be tracked (YES in S12), the internal communication unit 41 is the wireless communication device. 3 is transferred to the movement route prediction unit 42.
In the movement route prediction unit 42, first, the data acquisition unit 421 receives data acquired by the internal communication unit 41 (S13).

Next, the position estimation unit 422 refers to the radio wave intensity DB 425 and acquires learning data regarding the radio wave intensity from the radio wave intensity DB 425.
In the learning data, the value of the radio wave intensity at each point at a plurality of points in the target area of the mobile terminal cooperative mobile tracking system 1 obtained by learning is shown.
Based on the learning data acquired above and the value of the current radio wave intensity acquired by the data acquisition unit 421, the position estimation unit 422 estimates the current position of the tracking target person holding the mobile terminal device 2 (S15).
The current position is represented by coordinates on the map of the target area of the mobile terminal cooperative mobile tracking system 1.
The radio wave intensity learning data is data in which the coordinates of a plurality of points in the target area are associated with radio wave measurement values (radio wave intensity values) from the wireless communication devices 3 _{1 to} 3 _n .
That is, the value of the radio wave intensity from each of the wireless communication devices 3 _{1 to} 3 _n measured at the point A in the target area, and from each of the wireless communication devices 3 _{1 to} 3 _n measured at the point B in the target area. For each point, the value of the radio field intensity measured at that point is shown as the value of the radio field intensity of the radio wave.
Also, the learning data may be a measured value at each of the transmitted radio waves of the wireless communication device 3 ₁ to 3 _n from each point in the plurality of points in the target area (the value of radio field intensity).
That is, the radio wave intensity value measured by each of the wireless communication devices 3 _{1 to} 3 _n for the radio wave transmitted from the point A in the target area, and the radio wave transmitted from the point B in the target area to the wireless communication devices 3 _{1 to} 3 _n For each point, the value of the radio wave intensity measured by each of the radio communication devices 3 _{1 to} 3 _n of the radio wave transmitted from the point may be indicated.
In this way, the learning data shows the value of the radio wave intensity measured in advance, but the position (coordinates) of the tracking target person estimated by the position estimation unit 422 and the radio wave intensity acquired by the data acquisition unit 421 are newly set. You may add to learning data.
The position estimation unit 422 uses the radio field intensity values of the wireless communication devices 3 _{1 to} 3 _n acquired by the data acquisition unit 421 and the radio field intensity values of the wireless communication devices 3 _{1 to} 3 _n for each point of the learning data. By comparison, a point having a value closest to the value of the radio wave intensity acquired by the data acquisition unit 421 is estimated as the current position of the tracking target person.

After the current position coordinates are estimated by the position estimation unit 422, the data extraction unit 423 refers to the movement route history DB 426 and acquires movement route history data related to the position estimated by the position estimation unit 422 (S16). .
The data extraction unit 423 may acquire information on the movement locus up to the current position of the person to be tracked as movement route history data.
As shown in FIG. 18, the movement route history data is data in which the time change of coordinates (x, y) on the map of the person to be tracked is recorded.
The coordinates on the movement route history data are the coordinates of the person to be tracked estimated using the radio wave intensity when the mobile terminal device 2 and the wireless communication device 3 communicate.
The movement route history data of FIG. 18 represents the movement route history of the tracking target person shown in FIG.
Further, the data extraction unit 423 may acquire information on the movement destination from the past current position of the tracking target person based on the user ID of the tracking target person.
Further, the data extraction unit 423 moves the destination from the current position of another person having the same attributes (age, gender, work place, destination, movement speed and movement direction based on sensor information) as the person to be tracked. May be obtained.
Next, the route prediction unit 424 predicts the movement route of the tracking target person based on the movement route history data extracted by the data extraction unit 423 (S17).
That is, the route prediction unit 424 moves the tracking target person to the current position, the movement destination of the tracking target person from the current position in the past, and the movement destination of the other person having the same attribute as the tracking target person from the current position. Based on at least one of the above, the movement path from the current position of the person to be tracked is predicted.
In addition, the route prediction unit 424 uses the movement direction, movement speed, and the like of the tracking target person measured by the acceleration sensor, the geomagnetic sensor, the gyro sensor, or the like of the mobile terminal device 2 to determine the movement path from the current position of the tracking target person. You may make it predict.
An example of a method for predicting the movement route of the route prediction unit 424 will be described later.
Further, the movement route history data is weighted according to the attribute of the person to be tracked (the weight is increased in the case of the person's movement route history), so that the movement route can be predicted with higher accuracy.
The movement route prediction unit 42 repeatedly performs the above prediction processing in fine time units, and constantly updates the prediction movement route.
Next, the travel route prediction unit 42 registers the predicted travel route in the travel route history DB 426 (S18).
Next, the movement route prediction unit 42 transmits the predicted movement route data to the imaging device control unit 43.

In the imaging device control unit 43, the travel route prediction data acquisition unit 431 acquires travel route prediction data from the travel route prediction unit 42.
Next, the imaging device control information generation unit 432 generates imaging device control information (S19).
Specifically, the imaging device control information generation unit 432 refers to the surrounding map DB 434 and the imaging device control information DB 435, and acquires the shootable range and the current shooting range of each imaging device 5.
Next, the imaging device control information generation unit 432 collates the shootable range of each imaging device 5 with the movement route of the tracking target person acquired by the movement route prediction data acquisition unit 431, and the movement route becomes the shootable range. A certain imaging device 5 is selected as the imaging device 5 that captures the person to be tracked.
Then, the imaging device control information generation unit 432 generates imaging device control information for controlling the PTZ of the selected imaging device 5.
In the imaging device control information DB 435, the installation position, installation direction, current PTZ information, imaging range, and the like of each imaging device 5 are stored as data.
The imaging device control information generation unit 432 determines the imaging device 5 that captures the tracking target person and its PTZ when the movement path on the map of the tracking target person is obtained by combining this with the information of the surrounding map. be able to.
The control command unit 433 designates the number of the imaging device 5 to be controlled by the imaging device control information generation unit 432 (multiple is possible), and transmits the imaging device control information to the designated imaging device 5 via the internal communication unit 436. (S20).
At this time, the control command unit 433 also registers the imaging device control information in the imaging device control information DB 435.

<Operation of Imaging Device 5>
In the imaging device 5, the internal communication unit 51 acquires imaging device control information.
The internal communication unit 51 transfers the imaging device control information to the PTZ control unit 52.
The PTZ control unit 52 changes the PTZ value of the imaging device 5 based on the imaging device control information.
In addition, the image acquisition unit 53 acquires a captured image, encodes the acquired image, and transmits data obtained by the encoding to the mobile terminal cooperation device 4 or the monitoring control device via the internal communication unit 51. To do.

<Operation of the entire system>
FIG. 9 shows a sequence diagram of the entire system.
FIG. 9 shows an example of the operation of the first embodiment, and does not limit the realization method.
First, a wireless signal is transmitted from the mobile terminal device 2 to each of the wireless communication devices 3 _{1 to} 3 _n .
After receiving, the wireless communication device 3 transmits the acquired information to the mobile terminal cooperation device 4.
After receiving the acquired information, the mobile terminal cooperation device 4 estimates the current position of the person to be tracked, predicts the travel route based on this, records the travel route prediction result in the travel route history DB 426, and selects the imaging device 5 The imaging device control information is generated.
Further, the mobile terminal cooperation device 4 transmits the imaging device control information to the selected imaging device 5.
When receiving the imaging device control information, the imaging device 5 controls the PTZ based on the imaging device control information.
Thereafter, the imaging device 5 transmits the captured image information to the mobile terminal cooperation device 4 and the monitoring control device.

<Example of system layout>
FIG. 10 shows an arrangement example of the wireless communication device 3 and the imaging device 5 according to the first embodiment.
FIG. 10 shows an example of the arrangement according to the first embodiment, and does not limit the arrangement method.
The person to be tracked holds the mobile terminal device 2.
The wireless communication device 3 is installed on the ceiling or the like.
The wireless communication device 3 and the imaging device 5 are connected to the mobile terminal cooperation device 4 via a network.

<Method of Predicting Travel Route by Route Prediction Unit 424>
Hereinafter, an example of a method for predicting the movement path from the current position of the person to be tracked performed in S17 of FIG. 8 will be described.

1) When the tracking target person has passed through the target area in the past When the route prediction unit 424 obtains the coordinates of the current position of the tracking target person, the past movement route history data that the tracking target person passed through the target area is obtained. Explore.
Next, the route prediction unit 424 acquires the coordinates closest to the current position from each of the past movement route history data obtained by the search.
Next, the route prediction unit 424 predicts the movement route by one of the following two methods.

1-1) Method of calculating similarity with past movement route and referring to movement route with the closest similarity The route prediction unit 424 tracks the current movement route history data of the tracking target person to the current position. The movement path (up to M frames before) of the target person is acquired.
In addition, the route prediction unit 424 acquires the movement route (up to M frames before) of the tracking target person to the coordinates closest to the current position from each of the past movement route history data of the tracking target person.
Then, the route prediction unit 424 calculates the similarity of the acquired travel route.
For example, the route predicting unit 424 may calculate the similarity between the current travel route and the past travel route by adding the distances between the coordinates of the same frame of the current travel route and the past travel route. It is done.
In this method, the smaller the sum of the distances between coordinates, the higher the similarity between the current travel path and the past travel path.
Note that if there is no identical frame between the current travel route and the past travel route, the route prediction unit 424 complements using the previous and subsequent frames.
The route prediction unit 424 calculates the similarity with the current travel route for each past travel route, and selects the past travel route with the highest similarity.
Then, the route predicting unit 424 sets the predicted movement position in the next frame of the person to be tracked as the advanced position on the selected movement route with the current movement speed.
The predicted movement position after the next frame can be obtained by repeating the same process for the predicted movement position that arrives at the next frame.

1-2) Method of calculating similarity with past travel route and weighting based on similarity The route prediction unit 424 calculates the similarity in 1-1) above, and calculates a similarity equal to or greater than a certain threshold ( Select several past movement paths that have a sum of distances between coordinates below a specific value).
Further, the route prediction unit 424 weights the selected past movement route according to the similarity.
Then, the route prediction unit 424 sets the predicted movement position in the next frame of the tracking target person as a weighted average of the positions of the movement destinations in the selected past movement route.

2) When the tracking target person passes through the target area for the first time The route prediction unit 424 uses the coordinates of the current position of the tracking target person, the current moving speed, and the current traveling direction to reach the time of the next frame. Calculate the predicted wax movement position.
For the calculation of the predicted movement position, an existing prediction calculation method can be used.
In addition, when there is nothing to be referred to in the tracking target person data, the route prediction unit 424 uses similar user data similar to the tracking target person.
As for the route prediction method, the same method as “1) When the tracking target person has passed through the target area in the past” can be used.
That is, the route prediction unit 424 performs the same processing using the movement history data of similar users.
Next, a method for selecting similar users will be described.
[Select similar users]
When the tracking target person registers the destination, the route prediction unit 424 selects another user who has registered the same or a nearby destination as the destination of the tracking target person as a similar user.
As shown in FIG. 18, the destination is registered in, for example, travel route history data.
When there are a lot of similar users, the route prediction unit 424 preferentially selects users who are close to the movement speed of the person to be tracked and personal data (gender, age, etc.).
By doing so, the estimation accuracy of the predicted movement position is improved.

*** Effect of the embodiment ***
As described above, in this embodiment, since the movement path of the person to be tracked on the map is grasped instead of the image analysis base, the person to be tracked is hidden by the shield on the image and is tracked. The tracking of the tracking target person can be continued even when the user cannot perform the tracking.
As described above, according to the present embodiment, the tracking target person can be tracked continuously, so that the next time the tracking target person appears on the image can be smoothly captured in the image.
Moreover, in the prediction of the movement route, the GPS (Global Positioning System) is not used, and the radio wave intensity of the wireless communication is used. Therefore, the movement route of the person to be tracked can be predicted even in a station premises or a commercial facility.
Further, in the present embodiment, the location of the tracking target person on the map can be acquired, and the imaging range on the map can be estimated from the installation information and PTZ control information of each imaging device, so that it is reflected in the image. The approximate position in the image of the person to be tracked can be specified.

Embodiment 2. FIG.
In the first embodiment described above, the movement path prediction of the tracking target person and the control of the imaging device are performed only by the radio wave intensity. Next, the image acquired by the camera is analyzed by the image analysis device. An embodiment in which results are also integrated to predict a movement route will be described.
In the mobile terminal cooperative moving body tracking system according to the present embodiment, an image analysis device that analyzes an image acquired by the imaging device is installed in the imaging device or at a location connected to the imaging device via a network.
Then, not only the estimation of the moving path based on the radio wave intensity but also the movement of the tracking target person shown on the image is used to correct the estimated current position and the PTZ control of the imaging apparatus.

  Hereinafter, the structure of the mobile terminal cooperation mobile body tracking system of this Embodiment is demonstrated using FIGS. 11-14.

*** Explanation of configuration ***
In FIG. 11, the system block diagram of the mobile terminal cooperation mobile body tracking system 6 which concerns on this Embodiment is shown.
Also in the mobile terminal cooperative mobile tracking system 6 according to the present embodiment, the mobile terminal device 2, the wireless communication device 3, the communication network A, and the wireless communication line are the same, and the details are omitted.
For other devices, only the differences from the first embodiment are described.
Hereinafter, the imaging devices 9 _{1 to} 9 _n may be collectively referred to as the imaging device 9.

<Mobile terminal cooperation device 7>
As illustrated in FIG. 12, the mobile terminal cooperation device 7 includes an internal communication unit 71, a tracking target data acquisition unit 72, a movement route prediction unit 73, and an imaging device control unit 74.
The mobile terminal cooperation device 7 of the present embodiment is connected to the image analysis device 8 via the communication network C.
The internal communication unit 71 transmits and receives data to and from the image analysis apparatus 8 in addition to transmission and reception of data to and from the imaging device 9 via the communication network C.
Also in the present embodiment, the mobile terminal cooperation device 7 corresponds to an example of a mobile tracking device.

<Image analysis device 8>
As shown in FIG. 13, the image analysis device 8 includes an internal communication unit 81, an image data acquisition unit 82, and an image analysis unit 83.
The image data acquisition unit 82 acquires image data captured by the imaging devices 9 _{1 to} 9 _n from the internal communication unit 81 via the communication network C.
The image analysis unit 83 analyzes the image data acquired by the image data acquisition unit 82.

<Imaging device 9>
As illustrated in FIG. 14, the imaging device 9 includes an internal communication unit 91, a PTZ (pan / tilt / zoom) control unit 92, and an image acquisition unit 93.
The internal communication unit 91 communicates with the image analysis device 8 in addition to communicating with the mobile terminal cooperation device 7 via the communication network C.
The PTZ control unit 92 controls pan / tilt / zoom of the imaging device 9 based on an instruction from the mobile terminal cooperation device 7.
The image acquisition unit 93 acquires an image captured by the imaging device 9 and transmits the image from the internal communication unit 91 to the image analysis device 8 via the communication network C.

*** Explanation of operation ***
Next, the operation of the mobile terminal cooperative moving body tracking system 6 according to the present embodiment will be described.
Note that the operations of the following two items are the same as those in the first embodiment, and thus description thereof is omitted. 1) Communication between the mobile terminal device 2 and the wireless communication device 3 2) Communication between the wireless communication device 3 and the mobile terminal cooperation device 4

<Operation of Imaging Device 9>
The imaging device 9 acquires imaging device control information from the internal communication unit 91.
The PTZ control unit 92 changes the PTZ value of the imaging device 9 based on the acquired imaging device control information.
Further, the image acquisition unit 93 acquires a captured image, encodes the image, and transmits the data obtained by the encoding via the internal communication unit 51 to the image analysis device 8 and the mobile terminal cooperation device 4 or monitoring control. Send to device etc.

<Operation of Image Analysis Device 8>
In the image analysis device 8, the image data acquisition unit 82 acquires data transmitted from the imaging device 9 via the internal communication unit 81.
Then, the image data acquisition unit 82 decodes the data and transmits the captured image captured by the imaging device 9 to the image analysis unit 83.
The image analysis unit 83 acquires tracking target data (image, gender, age, etc.) transmitted from the mobile terminal cooperation device 7.
Further, the image analysis unit 83 acquires a captured image captured by the imaging device 9 from the image data acquisition unit 82, and detects an image of the tracking target person from the captured image.
Then, the image analysis unit 83 analyzes the position of the tracking target person on the image and the movement information of the tracking target person, estimates the current position of the tracking target person on the map based on this, and further performs tracking. The moving direction of the target person is estimated.
Then, the image analysis unit 83 detects the position of the tracking target person on the image, the movement information of the tracking target person, the estimated current position of the tracking target person, the estimated moving direction, and the information of the imaging device 9 that acquired the captured image. The tracking target image or the like is transmitted to the mobile terminal cooperation device 7.

<Operation of Mobile Terminal Cooperation Device 7>
The internal configuration of the movement route prediction unit 73 of the mobile terminal cooperation device 7 is the same as that of the movement route prediction unit 42 shown in FIG.
However, the data acquisition unit 421 also acquires data transmitted from the image analysis device 8 in addition to the information transmitted from the mobile terminal device 2.
The data to be acquired is as described in the operation of the image analysis device 8 described above.
The position estimation unit 422 estimates the current position of the tracking target person using the method based on the radio wave intensity described in the first embodiment. For example, the image analysis unit 83 estimates the current position of the tracking target person estimated based on the radio wave intensity. Correction is performed based on the current position of the tracked person.
An example of the current position correction method will be described later.
In addition to the data of the first embodiment, the movement history information DB 426 also stores data acquired from the image analysis device 8 (described above).
The data extraction unit 423 extracts necessary learning data including information acquired from the image analysis apparatus 8 in addition to the information used in the first embodiment.
In addition, the route prediction unit 424 uses the movement direction of the tracking target estimated by the image analysis unit 83 instead of the movement direction of the tracking target person measured by the acceleration sensor, the geomagnetic sensor, the gyro sensor, or the like of the mobile terminal device 2. It is possible to predict the movement path of the tracking target person.
The other operations of the route prediction unit 424 are the same as those in the first embodiment.
Since the operation of the imaging device control unit 43 is the same as that of the first embodiment, the description thereof is omitted.

FIG. 15 shows an operation flow of the mobile terminal cooperation device 7.
The operation flow of FIG. 15 shows an example of processing for realizing the second embodiment, and does not limit the implementation method.
In FIG. 15, S31 to S34 are the same as S11 to S14 of FIG.
In S <b> 35, the movement path prediction unit 73 transmits the image analysis data from the image analysis device 8 (imaging device ID, the position of the tracking target person in the image, the estimated current position of the tracking target person, via the internal communication unit 71. The estimated movement direction (motion vector, etc.) of the tracking target person is acquired.
In S36, the current position of the mobile terminal device 2 is estimated based on these and the current radio wave intensity.
S37 is the same as S16 in FIG.
S38 is basically the same as S17 in FIG. 10, but as described above, the movement path may be predicted using the estimated movement direction of the person to be tracked by the image analysis device 8.
S39 to S41 are the same as S18 to S20 in FIG.

<Operation of the entire system>
FIG. 16 shows a sequence diagram of the entire system.
FIG. 16 shows an example of the operation of the second embodiment, and does not limit the realization method.
First, a wireless signal is transmitted from the mobile terminal device 2 to each of the wireless communication devices 3 _{1 to} 3 _n .
After receiving, the wireless communication device 3 transmits the acquired information to the mobile terminal cooperation device 7.
In parallel with the above operation, the imaging device 9 transmits the captured image to the image analysis device 8.
The image analysis device 8 performs image analysis after receiving the captured image from the imaging device 9, and the ID of the imaging device in which the image of the tracking target person is present in the captured image, the position of the tracking target person in the captured image (x , Y), an estimated current position on the target map based on the position of the tracking target person in the captured image, and motion vector information in the captured image of the tracking target person are calculated.
The image analysis device 8 analyzes the captured image in time series and calculates motion vector information.
Then, the image analysis device 8 transmits image analysis information to the mobile terminal cooperation device 7.
After receiving the image analysis information, the mobile terminal cooperation device 7 estimates the current position, estimates the movement route based on the current position, records the movement route estimation result in the movement route history DB 426, and generates control information for the imaging device. .
Further, the mobile terminal cooperation device 4 transmits the imaging device control information to the selected imaging device 5.
When receiving the imaging device control information, the imaging device 5 controls the PTZ based on the imaging device control information.
Thereafter, the imaging device 9 transmits the captured image to the image analysis device 8.
The imaging device 9 may transmit the captured image not only to the image analysis device 8 but also to the mobile terminal cooperation device 7 and the monitoring control device.
Moreover, you may transmit to the monitoring control apparatus via the image analysis apparatus 8 or the mobile terminal cooperation apparatus 7. FIG.

<Current Position Correction Method by Position Estimation Unit 422>
If the camera calibration (internal parameters, distortion coefficient, external parameters) is strictly performed and the coordinates on the map correspond to the image coordinates of the camera, the object to be tracked in the image by geometric transformation The position (x, y) of the tracking target person on the map coordinates can be estimated from the detected position (u, v) of the person, and the position (x, y) of the tracking target person on the map coordinates can be estimated in the image. The detection position (u, v) of the tracking target person can be estimated.
Since the geometric transformation of the camera is well known, the description is omitted.
In the present embodiment, it is assumed that the face image of the person to be tracked is registered in the image capturing apparatus 5 and that the image capturing apparatus 5 can perform person recognition using the face image of the person to be tracked registered.
The position estimation unit 422 basically uses the position estimated based on the radio wave intensity as the current position of the tracking target person. If the tracking target person moving can be recognized (person recognition) by the camera, the tracking target person The position obtained by converting the position on the image of the person into the coordinates on the map is the current position, and the estimated position based on the radio wave intensity is not used.
When the camera is calibrated strictly, it is expected that the accuracy of the estimated position is higher in the method using the camera than in the method using the radio wave intensity.
However, the person to be tracked may not be correctly recognized on the image.
Therefore, the position estimation unit 422 calculates the position on the image where the tracking target person is displayed when the position (coordinates) estimated by the radio wave intensity is captured by the camera (the camera can be calibrated). If so, it can be calculated by geometric transformation).
At this time, if the predicted display position of the tracking target person obtained by the calculation and the display position of the person recognized by the camera are significantly shifted, there is a possibility that the camera cannot correctly recognize the tracking target person.
For this reason, the position estimation unit 422 does not use the estimated position obtained by the person recognition of the camera, but uses the estimated position based on the radio field intensity.
Alternatively, the position (coordinates) estimated by the radio wave intensity can be searched again to perform person recognition again.
When the person is recognized again and the above calculation is performed, it is determined that the person to be tracked is correctly captured (the expected display position based on the estimated position from the radio wave intensity and the person display by the camera person recognition) When the position error is below a certain level), the position estimation unit 422 uses the position coordinates estimated by the person recognition of the camera.

*** Effect of the embodiment ***
In the second embodiment, in addition to the effects of the first embodiment described above, the captured image of the imaging apparatus is analyzed, the motion information of the tracking target person is detected, and this is used for the movement path prediction, thereby achieving more accuracy. It is possible to realize the prediction of a good movement path and the accompanying improvement in tracking accuracy.
In addition, by matching the position of the tracking target person in the captured image and the position of the tracking target estimated by the radio wave intensity, it is possible to prevent erroneous detection of the tracking target person. It can be used as a reference image for detection.
In addition, by matching the owner of the mobile terminal device with the tracking target person detected on the image, a specific target can be watched and monitored.
As the specific target, for example, a child, an elderly person, a small animal, or the like, which is small and is likely to be blocked by a surrounding person or structure and not appear in the camera image, can be considered.

*** Additional notes ***

As mentioned above, although embodiment of this invention was described, you may implement in combination of 2 or more among these embodiment.
Alternatively, one of these embodiments may be partially implemented.
Alternatively, two or more of these embodiments may be partially combined.
In addition, this invention is not limited to these embodiment, A various change is possible as needed.

In the above description, the tracking target is described as a person, but the tracking target may not be a person as long as the tracking target is a moving object.
For example, it may be an animal equipped with a wireless communication terminal device or a vehicle such as an automobile.

*** Explanation of hardware configuration ***
A hardware configuration example of the mobile terminal cooperation devices 4 and 7 will be described with reference to FIG.
The mobile terminal cooperation devices 4 and 7 are computers.
The mobile terminal cooperation devices 4 and 7 include hardware such as a processor 901, an auxiliary storage device 902, a memory 903, a communication device 904, an input interface 905, and a display interface 906.
The processor 901 is connected to other hardware via the signal line 910, and controls these other hardware.
The input interface 905 is connected to the input device 907.
The display interface 906 is connected to the display 908.

The processor 901 is an IC (Integrated Circuit) that performs processing.
The processor 901 is, for example, a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or a GPU (Graphics Processing Unit).
The auxiliary storage device 902 is, for example, a ROM (Read Only Memory), a flash memory, or an HDD (Hard Disk Drive).
The memory 903 is, for example, a RAM (Random Access Memory).
6 and 7 is realized by the auxiliary storage device 902 or the memory 903.
The communication device 904 includes a receiver 9041 that receives data and a transmitter 9042 that transmits data.
The communication device 904 is, for example, a communication chip or a NIC (Network Interface Card).
The input interface 905 is a port to which the cable 911 of the input device 907 is connected.
The input interface 905 is, for example, a USB (Universal Serial Bus) terminal.
The display interface 906 is a port to which the cable 912 of the display 908 is connected.
The display interface 906 is, for example, a USB terminal or an HDMI (registered trademark) (High Definition Multimedia Interface) terminal.
The input device 907 is, for example, a mouse, a keyboard, or a touch panel.
The display 908 is, for example, an LCD (Liquid Crystal Display).

The auxiliary storage device 902 includes an internal communication unit 41, a movement path prediction unit 42, an imaging device control unit 43, an internal communication unit 71, a tracking target data acquisition unit 72, a movement path prediction unit 73 shown in FIG. A program for realizing the functions of the constituent elements of the imaging device control unit 74 excluding the storage unit is stored.
That is, the auxiliary storage device 902 includes a data acquisition unit 421, a position estimation unit 422, a data extraction unit 423, a route prediction unit 424, a movement route prediction data acquisition unit 431, an imaging device control information generation unit 432, and a control command unit 433 ( In the following, a program that realizes the function of “unit” will be described.
This program is loaded into the memory 903, read into the processor 901, and executed by the processor 901.
Further, the auxiliary storage device 902 also stores an OS (Operating System).
Then, at least a part of the OS is loaded into the memory 903, and the processor 901 executes a program that realizes the function of “unit” while executing the OS.
In FIG. 17, one processor 901 is illustrated, but the mobile terminal cooperation apparatuses 4 and 7 may include a plurality of processors 901.
A plurality of processors 901 may execute a program for realizing the function of “unit” in cooperation with each other.
In addition, information, data, signal values, and variable values indicating the processing results of “unit” are stored in the memory 903, the auxiliary storage device 902, or a register or cache memory in the processor 901.

The “part” may be provided as “circuitry”.
Further, “part” may be read as “circuit”, “process”, “procedure”, or “processing”.
“Circuit” and “Circuitry” include not only the processor 901 but also other types of processing circuits such as a logic IC or GA (Gate Array) or ASIC (Application Specific Integrated Circuit) or FPGA (Field-Programmable Gate Array). It is a concept to include.

  DESCRIPTION OF SYMBOLS 1 Mobile terminal cooperation mobile body tracking system, 2 Mobile terminal apparatus, 3 Wireless communication apparatus, 4 Mobile terminal cooperation apparatus, 5 Imaging apparatus, 6 Mobile terminal cooperation mobile body tracking system, 7 Mobile terminal cooperation apparatus, 8 Image analysis apparatus, 9 Imaging device, 21 User ID acquisition unit, 22 Sensor information acquisition unit, 23 Wireless communication unit, 31 Wireless communication unit, 32 Data acquisition unit, 33 Internal communication unit, 41 Internal communication unit, 42 Moving path prediction unit, 43 Imaging device control 51, internal communication unit, 52 PTZ control unit, 53 image acquisition unit, 71 internal communication unit, 72 tracking target data acquisition unit, 73 movement path prediction unit, 74 imaging device control unit, 81 internal communication unit, 82 image data acquisition Unit, 83 image analysis unit, 91 internal communication unit, 92 PTZ control unit, 93 image acquisition unit, 421 data acquisition unit, 42 2 Position estimation unit, 423 data extraction unit, 424 route prediction unit, 425 radio wave intensity DB, 426 movement route history DB, 431 movement route prediction data acquisition unit, 432 imaging device control information generation unit, 433 control command unit, 434 map around DB, 435 Imaging device control information DB, 436 Internal communication unit.

Claims (9)

The radio wave intensity of radio waves from a radio terminal device moving with a mobile object, measured by each of a plurality of radio communication devices arranged separately in a target area, or the radio waves measured by the radio terminal device Based on at least one of the radio field strengths of radio waves from each of the communication devices, a current path of the mobile body is estimated, and a travel path prediction unit that predicts a travel path of the mobile body;
From the plurality of imaging devices, based on the imageable range of each of the plurality of imaging devices arranged separately in the target area and the movement path predicted by the movement route prediction unit, A moving body tracking apparatus comprising: an imaging apparatus control unit that selects an imaging apparatus that images the moving body that moves along a movement path. The imaging device controller is
The moving body tracking device according to claim 1, wherein control for photographing the moving body is performed on the selected imaging device. The imaging device controller is
The moving body tracking device according to claim 1, wherein control related to panning, tilting, and zooming is performed on the selected imaging device as control for photographing the moving body. The travel route prediction unit
Obtained by learning, the value of the radio wave intensity from each of the plurality of wireless communication devices measured for each point in the plurality of points in the target area, and the value measured by each of the plurality of wireless communication devices The mobile body tracking according to claim 1, wherein the current position of the mobile body is estimated using learning data indicating at least one of radio field intensity values of radio waves transmitted for each of a plurality of points in the target area. apparatus. The travel route prediction unit
A movement trajectory until the moving body reaches the current position, a movement destination of the moving body in the past from the current position, a movement destination of the other moving body having the same attribute as the moving body from the current position The moving body tracking device according to claim 1, wherein a moving path of the moving body is predicted based on at least one of a moving direction of the moving body and a moving speed of the moving body. The travel route prediction unit
Estimated based on radio wave intensity using the current position of the moving body that is captured by any one of the plurality of imaging apparatuses and analyzed by analyzing a captured image that includes the image of the moving body The moving body tracking device according to claim 1, wherein the current position of the moving body is corrected. The travel route prediction unit
The movement of the moving body based on the moving direction of the moving body estimated by analyzing a captured image captured by any one of the plurality of imaging apparatuses and including an image shooting image of the moving body. The moving body tracking apparatus according to claim 1, wherein a path is predicted. The computer is measured by each of a plurality of wireless communication devices arranged separately in a target area, and the radio wave intensity of a radio wave from a radio terminal device moving with a moving body or the radio terminal device Based on at least one of the radio field strengths of radio waves from each of a plurality of wireless communication devices, the current position of the moving body is estimated, and a moving path prediction step for predicting the moving path of the moving body;
The computer is configured to detect the plurality of imaging devices based on the photographing range of each of the plurality of imaging devices that are spaced apart in the target area and the movement path predicted by the movement route prediction step. The moving body tracking method which has an imaging device control step which selects the imaging device which image | photographs the said moving body which moves the said movement path | route from inside. The radio wave intensity of radio waves from a radio terminal device moving with a mobile object, measured by each of a plurality of radio communication devices arranged separately in a target area, or the radio waves measured by the radio terminal device Based on at least one of the radio field strengths of radio waves from each of the communication devices, the current position of the moving body is estimated, and a moving path prediction step for predicting the moving path of the moving body;
From the plurality of imaging devices, based on the imageable range of each of the plurality of imaging devices arranged separately in the target area and the movement path predicted by the movement route prediction step, The moving body tracking program which makes a computer perform the imaging device control step which selects the imaging device which images the said moving body which moves a movement path | route.

Images