JP5932850B2 - Information processing system, information processing method, information processing apparatus, information processing terminal, information processing program, and recording medium - Google Patents

Description

  The present application belongs to the technical fields of an information processing system, an information processing method, an information processing apparatus, an information processing terminal, an information processing program, and a recording medium. More specifically, the present invention belongs to the technical fields of an information processing system, an information processing method, an information processing terminal, an information processing program, an information processing program, and a recording medium that process image data captured by a moving body.

  Full parking availability information for parking lots is being obtained from traffic information such as VICS (registered trademark) (Vehicle Information and Communication System) through devices such as car navigation. Furthermore, a method for providing information on waiting time until entering a parking lot has been proposed. For example, in Patent Document 1 below, the time when the entrance wait is started is stored, and the waiting time is calculated by subtracting the entrance wait start time from the time when the entrance gate is passed or permitted to pass through. The rear vehicle stores the waiting time, and when a new trailing vehicle appears, the waiting time is transmitted to the vehicle, and the new trailing vehicle displays the waiting time. A display method is disclosed.

JP 2004-157717 A

  However, in the technique described in Patent Document 1, it is necessary to introduce equipment such as a parking gate that can communicate with a vehicle at a place where moving bodies such as a parking lot are arranged.

  Therefore, the present application has been made in view of the above-described problems, and an example of the problem is to provide an information processing system that can calculate waiting time without introducing new equipment, for example.

To solve the above problems, a first aspect of the present invention, a first acquiring means for acquiring image data obtained by shooting an image matrix comprising a plurality of mobile, an imaging time 及 beauty imaging location of at least the image data a second acquisition unit configured to acquired information, is calculated from (i) the length of the matrix is calculated from the image data, (ii) the imaging location information and the imaging time is two different images data that a moving distance of the first moving body of the plurality of moving body, a first calculating means for calculating the (iii) wait time of the the imaging time of the two image data, pressurizing et previous SL matrix, It is provided with.

The invention described in claim 6 is the information processing method of an information processing system for processing a first acquisition step of acquiring image data obtained by image shooting a matrix comprising a plurality of mobile imaging of at least the image data time 及 beauty a second obtaining step of acquired information related to the imaging location, (i) the length of the image data the matrix that will be calculated from, (ii) the imaging location information and the imaging time is two different is calculated from the images data, calculating a moving distance of the first moving body of the plurality of moving bodies, a (iii) wait time of the the imaging time of the two image data, pressurizing et before Symbol matrix and step out calculation you, characterized in that it comprises a.

The invention of claim 9 causes a computer, first acquisition means for acquiring image data of the captured matrix comprising a plurality of mobile, first to obtain information about the imaging time and imaging locations of at least the image data second obtaining means, and, (i) the length of the image data the matrix that will be calculated from, (ii) the imaging place information, and the imaging time of the is calculated from the two different images data, said plurality of features and 1 travel distance of the moving body of the moving body, that is function as the first calculating means, for calculating a waiting time of the matrix from the imaging time (iii) the two image data And
The invention according to claim 10 is characterized in that the information processing program according to claim 9 is recorded so as to be readable by the computer.

It is a block diagram which shows an example of schematic structure of the information processing system which concerns on embodiment. It is a schematic diagram which shows an example of schematic structure of the information processing system which concerns on an Example. It is a block diagram which shows an example of schematic structure of the information processing server which concerns on an Example. It is a schematic diagram which shows an example of the image database of the memory | storage part of the information processing server which concerns on an Example. It is a schematic diagram which shows an example of the waiting time database of the memory | storage part of the information processing server which concerns on an Example. Is a block diagram showing an example of a schematic configuration of the engagement Ru vehicle mounting the information processing apparatus in the examples. It is a sequence diagram which shows an example of the operation | movement of waiting time calculation in the information processing system which concerns on an Example. It is a schematic diagram which shows an example of the waiting state for warehousing in a parking lot. It is a schematic diagram which shows an example of the pattern of the matrix of vehicles. It is a schematic diagram which shows an example of the pattern of the matrix of vehicles. It is a sequence diagram which shows an example of the operation | movement of waiting time output in the information processing system which concerns on an Example. It is a schematic diagram which shows an example of the display screen of prediction waiting time. It is a schematic diagram which shows an example of the waiting state for warehousing in a parking lot.

  An embodiment for carrying out the present application will be described with reference to FIG. FIG. 1 is a block diagram illustrating an example of a schematic configuration of the information processing system according to the embodiment.

1, the information processing system 1 includes a first obtaining unit 1a, a second acquisition unit 1b, and is configured to include a first calculation unit 1e, a.

First obtaining means in this configuration 1a acquires image data obtained by shooting an image matrix comprising a plurality of mobile. An example of this moving body, a vehicle such as an automobile, motorcycle, bicycle, human and the like. As an example of a place where the moving body lined, vehicle-lined parking lot, and a store like people are lined up. An example of acquisition of the image data, a case of acquiring a camera or the like or al image data, when obtaining from the storage means the image data has been stored, or the like when acquiring the image data through the network and the like.

The second acquisition unit 1b is acquired information on imaging time 及 beauty imaging location of at least the image data. Here, as an example of the information acquired by the second acquiring unit 1b, in addition to the imaging time of the image data such as an imaging time of the image data, the imaging Place the image data information (current position data), the image data position information of the parking lot in the vicinity of the destination as an imaging location, traveling direction and their orientation in the image pickup direction to moving body image data, installation direction, etc. of an imaging unit and the like.

First calculating means 1e is calculated from (i) the length of the matrix is calculated from the image data, (ii) the imaging location information and the imaging time is two different images data, wherein calculating a moving distance of the first moving body of the plurality of mobile, the (iii) the imaging time of the two image data and, wait time of the pressurized et previous SL matrix.

As described above, according to the operation of the information processing system 1 according to the embodiment, image data obtained by imaging a matrix composed of a plurality of moving objects is acquired, and at least regarding the imaging time and the imaging location of the acquired image data. Get information. Then, (i) the length of the matrix calculated from the image data, and (ii) the movement of one moving body among a plurality of moving bodies calculated from two pieces of image data with different imaging location information and imaging time and the distance, by calculating the waiting time matrix from the imaging time (iii) 2 pieces of image data, in a place where the moving body arranged, becomes unnecessary introduction of new equipment, the waiting time at the location where the moving body lined Can be calculated.

(Example)
[1. Overview of information processing system configuration and functions]

Next, specific examples corresponding to the above-described embodiment will be described with reference to FIGS. Note embodiment described below, embodiments of the application of the information processing terminal mounted on vehicles or the like, the present application to the information processing in the information processing system and information processing server connected through a network as an example of an information processing apparatus It is an example.

2, the information processing system 1 as an example of the information processing system 1 according to the embodiment, parking information processing server 10 for calculating the waiting time in (an example of where moving body are arranged) (an information processing apparatus as an example) of includes an example of a vehicle information processing apparatus (information processing apparatus mounted in the vehicle both 5, an example of the information processing terminal) 20, a.

  The information processing server 10 calculates a waiting time based on the image data acquired from the in-vehicle information processing device 20 of the vehicle 5, and provides waiting time information to the in-vehicle information processing device 20 of the vehicle 5 that has been requested. The information processing server 10 functions as a computer.

  The in-vehicle information processing device 20 captures image data when passing through the vicinity of the parking lot, or requests the provision of waiting time information of the parking lot. Moreover, the vehicle-mounted information processing apparatus 20 functions as a computer.

  The information processing server 10 and the in-vehicle information processing apparatus 20 can transmit and receive data to and from each other via the network 3 using, for example, TCP / IP as a communication protocol. The network 3 is constructed by, for example, the Internet, a dedicated communication line (for example, CATV (Community Antenna Television) line), a mobile communication network (including a base station), a gateway, and the like.

[2. Configuration and function of information processing server and each terminal device]
(2.1 Configuration and Function of Information Processing Server 10)
Next, the configuration and function of the information processing server 10 will be described with reference to FIGS.

  FIG. 3 is a block diagram illustrating an example of a schematic configuration of the information processing server 10. FIG. 4 is a schematic diagram illustrating an example of an image database in the storage unit of the information processing server 10. FIG. 5 is a schematic diagram illustrating an example of a waiting time database in the storage unit of the information processing server 10.

As shown in FIG. 3, the information processing server 10 includes a communication unit 11 (an example of the first acquisition unit 1a and an example of the second acquisition unit 1b ) that communicates with the in-vehicle information processing device 20 of the vehicle 5. a storage unit 12 for storing image data received from the vehicle information processing apparatus 20 (an example of the waiting time storage means), an image analysis unit 1 3 for recognizing such receipts queue from the image data, the image analyzer 13 The time calculation unit 14 (an example of the first calculation unit 1e) that calculates the prediction waiting time from the analysis result of the above and the storage unit 12 from the storage unit 12 when there is a request from the in-vehicle information processing device 20, predicts waiting for entry of the corresponding parking lot An analysis result extraction unit 15 that extracts time, an analysis result output unit 16 that temporarily stores analysis results and the like to output analysis results, and a control unit 17 that controls each process of the communication unit 11 and the like .

  The communication unit 11 is connected to the network 3 and controls the communication state with the in-vehicle information processing apparatus 20. And the communication part 11 receives the image data imaged from the vehicle 5, the imaging time of image data, the positional information of the vehicle 5, and the information of the imaging direction of image data from the vehicle-mounted information processing apparatus 20 of the vehicle 5. In addition, the communication unit 11 receives an output request for the predicted waiting time from the in-vehicle information processing device 20 of the user's vehicle 5 who wants information on the predicted waiting time, or sends the predicted waiting time to the in-vehicle information processing device 20 of the vehicle 5. Or send results.

  The storage unit 12 is configured by, for example, a hard disk drive or the like, and stores an image database (image DB) 12a that stores image data transmitted from the in-vehicle information processing device 20, and a waiting time that stores the calculated predicted waiting time. And a time database (waiting time DB) 12b.

  The storage unit 12 stores the image data transmitted from the in-vehicle information processing apparatus 20 in association with the imaging time, the imaging location, the imaging direction, and the vehicle ID of the vehicle 5. The storage unit 12 also captures image data such as the image data capture time (an example of image data capture time), the current position of the vehicle 5 as the image data capture location, and the vehicle 5 travel direction as the image data capture direction. Store related information.

  As illustrated in FIG. 4, the image data is stored in the storage unit 12 in association with the image data capture time, the image capture location, the image capture direction, and the vehicle ID of the vehicle 5, and the image database 12 a is constructed. . In addition, as an example of the imaging direction of image data, the traveling direction of the vehicle 5 and the set height of the imaging means in the vehicle 5 can be given.

  As shown in FIG. 5, in the storage unit 12 as an example of the predicted waiting time storage means, the calculated predicted waiting time includes a change amount of the waiting time per predetermined time, a parking lot ID indicating a parking lot, and a parking lot. The waiting time database 12b is constructed in association with the location information, image data obtained by imaging the matrix near the parking lot, and the data update time.

  In addition, the storage unit 12 stores a template such as an image of one car, an image of cars arranged in a row, and feature quantities of these images.

  The storage unit 12 stores various programs such as an operating system and a server program. Note that the various programs may be acquired from, for example, another server device via the network 3, or may be recorded on a recording medium and read via a drive device.

  The image analysis unit 13 includes, for example, an LSI (Large Scale Integration) for image analysis, and recognizes a warehousing queue and identifies a parking lot from a captured image. In addition, the image analysis unit 13 compares the image of the same parking lot that was previously captured with the queuing queue, and obtains the moving distance of the vehicle waiting for warehousing.

  The waiting time calculation unit 14 has a function of a CPU (Central Processing Unit) and the like, calculates a time difference when the two images comparatively analyzed by the image analysis unit 13 are captured, and calculates the time difference and the image analysis unit 13. The predicted waiting time is calculated from the moving distance of the vehicle obtained in step (1).

  The analysis result extraction unit 15 stores the predicted waiting time of the corresponding parking lot in the storage unit 12 when there is an output request of the predicted waiting time from the in-vehicle information processing device 20 of the user's vehicle 5 that wants information on the predicted waiting time. Read from the waiting time database 12 b and pass to the analysis result output unit 16.

  The analysis result output unit 16 includes, for example, a RAM (Random Access Memory), and temporarily stores the predicted waiting time data read from the waiting time database 12b when there is predicted waiting time data. Temporarily store data indicating that there is no estimated waiting time.

  The control unit 17 includes, for example, a CPU, and controls the operation of each processing unit of the information processing server 10.

(2.2 Configuration and function of in-vehicle information processing apparatus 20)
Next, the configuration and function of the in-vehicle information processing apparatus 20 will be described with reference to FIG.
FIG. 6 is a block diagram illustrating an example of a schematic configuration of the in-vehicle information processing apparatus 20 mounted on the vehicle 5.

As illustrated in FIG. 5, the in-vehicle information processing apparatus 20 includes a communication unit 21 that communicates with the information processing server 10, an imaging unit 22 that captures a landscape in the traveling direction of the vehicle 5 (an example of a first acquisition unit), An image detection unit 23 that detects an image area that may be a queuing queue from an image captured by the imaging unit 22, and a current location acquisition unit 24 that acquires information on the current position of the vehicle 5 (an example of second acquisition means). A time acquisition unit 25 (an example of a second acquisition unit) that acquires an imaging time by the imaging unit 22, an analysis result output unit 26 that displays a predicted waiting time, and a memory that stores captured image data and the like A unit 27, a parking lot search unit 28 (an example of a second acquisition unit) that searches for a parking lot near the destination, and a control unit 29 that controls the operation of each unit of the in-vehicle information processing apparatus 20.

  The communication unit 21 is connected to the network 3 and controls the communication state with the information processing server 10. The communication unit 21 transmits the captured image data, the position information of the vehicle 5 itself, the current time as the imaging time of the image data, the information on the traveling direction of the vehicle 5 as the imaging direction of the image data, and the like to the information processing server 10. . Further, when the user wants information on the predicted waiting time, an output request for the predicted waiting time is transmitted to the information processing server 10 and the result of the predicted waiting time is received.

  The imaging unit 22 as an example of an imaging unit is a digital camera having an imaging element such as a charge coupled device (CCD) image sensor or a complementary metal oxide semiconductor (CMOS) image sensor. The imaging unit 22 is installed at a position where the front of the vehicle 5 can be imaged, such as near the rearview mirror of the vehicle 5. The imaging unit 22 captures a peripheral image in front of the vehicle 5. Note that the installation position of the imaging unit 22 may be on the side or rear of the vehicle 5, and the side or rear may be imaged. In addition, a plurality of imaging units 22 may be provided.

  The image detection unit 23 includes, for example, an LSI or CPU for image analysis, and detects an image area that may be a queuing queue from the image data captured by the imaging unit 22. In addition, since the detailed process regarding image processing is performed in the information processing server 10, the image detection unit 23 detects an image that may be a matrix.

  The current location acquisition unit 24 includes a GPS (Global Positioning System) sensor and the like. The current location acquisition unit 24 receives navigation radio waves from GPS satellites on the satellite orbit and detects the position, altitude, speed, and the like of the vehicle 5 on which the in-vehicle information processing device 20 is mounted.

  The time acquisition unit 25 acquires the current time from a GPS sensor, a built-in timer, or the like.

Analysis result output unit 26, a liquid crystal display device or EL (Electro Luminescence) display, such as a device, and a speaker. The analysis result output unit 26 displays the predicted waiting time acquired from the information processing server 10 and an image around the current parking lot, and provides information on the predicted waiting time by voice.

  The storage unit 27 is configured by, for example, a hard disk drive or the like, and stores the image data captured by the imaging unit 22 in association with the position information of the vehicle 5, the current time, and the like. Further, the storage unit 27 stores a template such as an image of one car, an image of a plurality of cars arranged, and feature amounts of these images.

  The parking lot search unit 28 searches for a parking lot near the destination by a destination setting function such as a car navigation device. In addition, since the route search technique in a car navigation apparatus etc. is a well-known technique, description is abbreviate | omitted here.

The control unit 29 has a CPU, for example, and controls the operation of each processing unit of the in-vehicle information processing apparatus 20.
[3. Operation of information processing system]
Next, the operation of the information processing system 1 according to the embodiment will be described with reference to FIGS.

(3.1 Example of calculation of predicted waiting time)

An example of the operation for calculating the predicted waiting time will be described with reference to FIGS.
FIG. 7 is a sequence diagram illustrating an example of a waiting time calculation operation in the information processing system according to the embodiment. FIG. 8 is a schematic diagram illustrating an example of a waiting state for storage in a parking lot. FIG. 9 and FIG. 10 are schematic diagrams showing examples of vehicle matrix patterns.

  First, it is assumed that the engine of a certain vehicle 5 is started and the power of the in-vehicle information processing apparatus 20 is turned on. Assume that the vehicle 5 starts to travel on the road.

  As shown in FIG. 7, the in-vehicle information processing apparatus 20 acquires image data (step S1). Specifically, the imaging unit 22 captures a landscape from the vehicle 5 to obtain information such as traffic conditions and acquires image data. Then, the imaging unit 22 outputs the acquired image data to the image detection unit 23. The image detection unit 23 acquires image data from the imaging unit 22. In addition, as shown in FIG. 8, when the imaging part 22 is installed in front of the vehicle 5 and images a front landscape, image data relating to the front landscape is acquired. Moreover, the vehicle-mounted information processing apparatus 20 may acquire image data in a plurality of directions of front, side, and rear image data.

  Next, the in-vehicle information processing apparatus 20 acquires current position data (step S2). Specifically, the current location acquisition unit 24 acquires current location data of the vehicle position from GPS information of a GPS sensor or the like.

  Next, the in-vehicle information processing device 20 determines whether or not there is a parking lot around the current position (step S3). Specifically, the parking lot search unit 28 searches for a position of a parking lot near the vehicle position from a database such as a car navigation system based on the acquired current position data. Further, the parking lot search unit 28 acquires the traveling direction of the vehicle 5 from the current location acquisition unit 24 or the sensor of the own vehicle, and specifies the imaging direction of the imaging unit 22. And the parking lot search part 28 considers the direction of the imaging of the imaging part 22, and specifies a parking lot. If the location information of the parking lot and the location information of the current location are within a predetermined distance, the in-vehicle information processing device 20 determines that there is a parking lot around the current location.

  When it is determined that there is no parking lot around the current position (step S3; NO), the in-vehicle information processing apparatus 20 returns to the process of step S1 in which the imaging unit 22 images the traffic situation and the like.

  When it is determined that there is a parking lot around the current position (step S3; YES), the in-vehicle information processing device 20 detects a matrix from the image data (step S4). Specifically, the image detection unit 23 performs image analysis such as differentiation processing on the acquired image data, extracts a contour and the like, and detects an image area that is likely to have a warehousing queue. With reference to the storage unit 27, image analysis may be performed based on an image template or a feature amount, and an image region that is likely to have a warehousing queue may be extracted. The image detection unit 23 extracts a stationary image from a series of image data captured while passing near the parking lot, compared with the image data captured several seconds ago (frame difference), and the storage unit 27 Referring to FIG. 4, a matrix of vehicles or the like may be detected. In this process, all possible queuing queues may be detected, and the final determination of the queuing queue may be performed by the information processing server 10.

  Next, the in-vehicle information processing device 20 determines whether or not there is a matrix (step S5). Specifically, when the image detection unit 23 detects a matrix, it is assumed that the matrix exists, and when the matrix cannot be detected, it is assumed that no matrix exists.

  When it is determined that there is no queue (step 5; NO), the in-vehicle information processing device 20 determines that the queue is not a warehousing queue, and returns to the processing of step S1 in which the imaging unit 22 images the traffic situation and the like.

  If it is determined that there is a matrix (step 5; YES), the in-vehicle information processing device 20 acquires the current time (step S6). Specifically, the time acquisition unit 25 acquires the current time from a GPS sensor, a built-in timer, or the like.

  Next, the in-vehicle information processing device 20 transmits image data or the like (step S7). Specifically, the communication unit 21 detects the current position data (imaging position information) as the image data imaging location, the current time as the image data imaging time (imaging time), and the vehicle 5 as the image data imaging direction. Data on the traveling direction and the height of the imaging unit 22 from the ground (the set height of the imaging unit 22), image-related information such as the vehicle ID of the host vehicle, and image data are wirelessly transmitted to the information processing server 10. It transmits via network 3 by communication. You may transmit the parking lot positional information and parking lot ID of an example of image related information.

  Next, the in-vehicle information processing apparatus 20 determines whether or not the process is finished (step S8). Specifically, the control unit 29 checks the ON / OFF state of the power switch.

  Next, when the processing is not completed (when the power switch is ON) (step S8; NO), the in-vehicle information processing device 20 returns to the processing of step S1 and acquires image data. In addition, when the process ends (when a signal for turning off the power switch is received) (step S8; NO), the in-vehicle information processing apparatus 20 ends the process.

  Next, the information processing server 10 receives image data or the like (step S10). Specifically, the communication unit 11 receives image data and image related information from the in-vehicle information processing device 20 via the network 3. Then, the information processing server 10 stores the received image data in the image database 12a of the storage unit 12 in association with the image related information. Note that the time when the information processing server 10 receives the image data may be used instead of the imaging time.

  Next, the information processing server 10 calculates a matrix length (step S11). Specifically, the image analysis unit 13 analyzes the image received from the in-vehicle information processing apparatus 20 and extracts a partial region of the matrix as in step S4. Then, as shown in FIG. 8, the image analysis unit 13 sets the matrix length L1 at the imaging time t = t2 when the imaging time t = t1, based on the imaging direction of the image data and the set height of the imaging unit 22. In this case, the matrix length L2 is calculated. More specifically, the image analysis unit 13 refers to a series of image data captured while a certain vehicle 5 passes near the parking lot, with reference to the image database 12a of the storage unit 12, the vehicle ID, and the imaging time. The imaging position information, the traveling direction, and the set height of the imaging unit 22 are specified. Then, the image analysis unit 13 calculates a matrix length from the specified series of image data by image analysis.

  Next, the information processing server 10 acquires image data and the like with different imaging times around the same parking lot (step S12). Specifically, as shown in FIG. 8 (when t = t2), when the time when the image data from the vehicle 5 is acquired is approximately t = t2, the image analysis unit 13 captures the acquired image data. With reference to the image database 12a, image data having imaging position information that is the same as or close to the position information is acquired for a predetermined time (for example, 5 to 15 minutes) or more from the imaging time t2 of the acquired image data (for example, Search image data within 2 to 24 hours). Then, the image analysis unit 13 extracts the latest image data at the previous time from the searched image data (for example, as shown in FIG. 8 (in the case of t = t1), another image data is obtained at t = t1. Image data from the vehicle 5).

  Further, the image analysis unit 13 refers to the image database 12a based on the received parking lot position information and parking lot ID or the parking lot position information and parking lot ID specified from the imaging position information of the image data. Image data having imaging position information that is the same as or close to the imaging position information of the acquired image data may be searched.

Next, the information processing server 10, the calculating the moving distance of the moving body (step S13) Specifically, the image analysis unit 13, also with respect to the image data by the imaging time is different, as in step S11, the matrix Extract the image of the partial area. Then, as shown in FIG. 9, the image analysis unit 13 arranges the vehicle in the image of the queue of the vehicle at the imaging time t = t1 and the arrangement of the vehicle in the image of the queue of the vehicle at the imaging time t = t2. and a pattern, based on the imaging direction of the image data, calculating the deviation of the arrangement pattern, the moving distance of the moving body. As an example of the arrangement pattern of vehicles, there are a vehicle shape pattern, a color pattern, and the like in a queue.

Further, as shown in FIG. 8, the two image data by the imaging time is different, identifies the vehicle 6 that are common among the vehicles are arranged as one example of a side-by-side have that moving body (an example of a moving body), specific The travel distance D of the vehicle 6 may be calculated from the two image data. Further, as shown in FIG. 10, in two image data having different imaging times, common vehicles are identified from among the vehicles arranged side by side, and the movement distances D1, D2, and D3 of the identified vehicles are set to 2 One of calculated from the image data, the moving distance of the average or as a moving distance of the moving body.

Next, the information processing server 10 calculates a predicted waiting time (step S14). Specifically, the prediction waiting time calculation unit 14 reads out the imaging times t1 and t2 of the two image data whose movement distances are calculated in step S14 from the image database 12a, and the time difference (2) when these two images are captured. An example of imaging time of two image data) is obtained. Then, the predicted waiting time is calculated from the time difference (t2−t1), the predicted waiting time calculating unit 14 using the matrix length L calculated in step S11, and the moving distance D calculated in step S13. ).
Travel distance per time Dt = D / (t2−t1) (1)
Predictive waiting time T = L / D (2)

  Next, the information processing server 10 determines whether or not it is different from the previous waiting time (step S15). Specifically, the predicted waiting time calculation unit 14 refers to the waiting time database 12b based on the parking lot ID or the parking lot position information, and the update waiting time of the latest predicted waiting time close to the imaging time t = t2. Read data. Then, the predicted waiting time calculation unit 14 compares the calculated predicted waiting time with the read predicted waiting time, and determines whether or not it is different from the previous waiting time.

  If it is not different from the previous waiting time (step S15; NO), the information processing server 10 performs the process of step S18.

  If it is different from the previous waiting time (step S15; YES), the information processing server 10 corrects the predicted waiting time (step S16). Specifically, the predicted waiting time calculation unit 14 obtains a difference (waiting time change amount) between the calculated predicted waiting time and the read predicted waiting time, and the predicted waiting time is determined according to the increase amount or the decrease amount. , Correct the estimated waiting time. Furthermore, the predicted waiting time calculation unit 14 may read the waiting time change amount data with reference to the waiting time database 12b and correct the predicted waiting time according to the tendency of the waiting time change amount. For example, when the amount of change in waiting time increases by 5 minutes per 10 minutes of the predetermined time, the waiting time after 30 minutes may be calculated as the calculated waiting time +15 minutes, and the corrected waiting time may be obtained.

  Next, the information processing server 10 stores the predicted waiting time (step S17). Specifically, the predicted waiting time calculation unit 14 writes the corrected predicted waiting time, waiting time variation per hour, parking lot ID, and image data in association with each other in the waiting time database 12b.

  Next, the information processing server 10 determines whether the process is finished (step S18). Specifically, the control unit 17 checks the ON / OFF state of the power switch.

  Next, when the processing is not completed (when the power switch is ON) (step S18; NO), the information processing server 10 returns to the processing of step S10 and waits for reception of image data or the like. Further, when the process is completed (when a power switch OFF signal is received) (step S18; NO), the information processing server 10 ends the process.

  Note that the in-vehicle information processing apparatus 20 may omit the processes of step S3 and step S4.

(3.2 Example of operation for requesting predicted waiting time)
Next, an example of an operation for requesting a predicted waiting time will be described with reference to FIGS. 11 and 12.
FIG. 11 is a sequence diagram illustrating an example of a waiting time output operation in the information processing system according to the embodiment. FIG. 12 is a schematic diagram illustrating an example of a display screen for a predicted waiting time.

  First, the in-vehicle information processing device 20 searches for a parking lot near the destination (step S20). Specifically, when a user sets a destination by car navigation or the like, the parking lot search unit 28 searches for a parking lot near the destination and obtains parking lot position information or a parking lot ID.

  Next, the vehicle-mounted information processing apparatus 20 transmits the parking lot position information (step S21). Specifically, in order to obtain a predicted waiting time for entering the corresponding parking lot, the communication unit 21 sends a parking waiting predicted waiting time output request to the parking lot position information, the parking lot position information or the parking lot ID, The vehicle ID of the vehicle is transmitted to the information processing server 10 via the network 3 by wireless communication. The communication unit 21 may transmit the parking lot position information and the parking lot ID to the information processing server 10.

  Next, the information processing server 10 receives parking lot position information (step S22). Specifically, the communication unit 11 receives a predicted waiting time output request, parking lot position information or parking lot ID, vehicle ID, and the like from the in-vehicle information processing device 20 via the network 3.

  Next, the information processing server 10 searches for a predicted waiting time (step S23). Specifically, when a predicted waiting time output request is received from the in-vehicle information processing device 20, the analysis result extraction unit 15 refers to the waiting time database 12b and has a request based on the parking lot position information or the parking lot ID. The predicted waiting time of the parking lot is searched from the storage unit.

  Next, the information processing server 10 determines whether or not the requested parking waiting time for the parking lot exists (step S24). Specifically, if the analysis result extraction unit 15 obtains the search result and the update time is within a predetermined time (for example, within 24 hours) from the current time, there is a predicted waiting time for the requested parking lot. Then.

  If the requested waiting time for the parking lot exists (step S24; YES), the information processing server 10 passes the predicted waiting time to the analysis result output unit 16 (step S25). Specifically, the analysis result extraction unit 15 passes the predicted waiting time, image data, and the like read out by searching to the analysis result output unit 16.

  When the requested waiting time for the parking lot does not exist (step S24; NO), the information processing server 10 passes information on the absence of the predicted waiting time to the analysis result output unit 16 (step S26). Specifically, the analysis result extraction unit 15 passes the result “not present” to the analysis result output unit 16.

  Next, the information processing server 10 transmits the result (step S27). Specifically, the communication unit 11 networked the result (predicted waiting time and image data or “not present” result) input to the analysis result output unit 16 based on the vehicle ID to the in-vehicle information processing device 20. 3 to transmit.

  Next, the information processing server 10 determines whether the processing is finished (step S28). Specifically, the control unit 17 checks the ON / OFF state of the power switch.

  Next, when the processing is not finished (when the power switch is turned on) (step S28; NO), the information processing server 10 returns to the processing of step S22 and waits for reception of a request for a predicted waiting time. . Further, when the process is completed (when a power switch OFF signal is received) (step S28; NO), the information processing server 10 ends the process.

  Next, when the information processing server 10 transmits the result, the in-vehicle information processing device 20 receives the result (step S30). Specifically, the communication unit 21 receives the predicted waiting time and image data, or the result of “does not exist” from the information processing server 10 via the network 3.

  Next, the in-vehicle information processing device 20 determines whether or not the estimated waiting time has been acquired (step S31). When there is a response from the information processing server 10 before time-out, the in-vehicle information processing device 20 confirms whether or not the received predicted waiting time has been acquired.

  When the predicted waiting time is acquired (step S31; YES), the in-vehicle information processing device 20 displays an image indicating the predicted waiting time and the state of the queue (step S32). Specifically, as illustrated in FIG. 12, the in-vehicle information processing apparatus 20 displays an image indicating the predicted waiting time and the queue on the analysis result output unit 26. Note that the in-vehicle information processing apparatus 20 may output information on the predicted waiting time from the speaker of the analysis result output unit 26 by voice.

  When the waiting waiting time has not been acquired (step S31; NO), the in-vehicle information processing device 20 displays information indicating that the waiting time is not present (step S33). Specifically, the in-vehicle information processing apparatus 20 displays on the analysis result output unit 26 that the predicted waiting time cannot be acquired, such as “the predicted waiting time is zero”.

  Next, the in-vehicle information processing apparatus 20 determines whether or not the process is finished (step S34). Specifically, the control unit 29 checks the ON / OFF state of the power switch.

  Next, when the processing is not completed (when the power switch is turned on) (step S34; NO), the in-vehicle information processing device 20 returns to the processing of step S20 and searches for a parking lot near the destination. Wait for reception. In addition, when the process ends (when a signal for turning off the power switch is received) (step S34; NO), the in-vehicle information processing apparatus 20 ends the process.

  Note that the in-vehicle information processing device 20 does not have to be installed in all vehicles that request the predicted waiting time. The vehicle that requests the predicted waiting time has a device that can be connected to the information processing server 10 via the network 3, and the device only needs to acquire and output information on the predicted waiting time.

As described above, according to the operation according to the embodiment, moving body (for example, the vehicle 6 and the like) where the lined (e.g., parking) car For example the moving body that is lined the in both five et imaging acquires image data, acquires image related information including information on imaging time and imaging locations of the image data, the length of the side by side have that moving body of the matrix, calculated from the image data, the information of the imaging location based, calculated from the two different said image data imaging time, from alongside calculates the moving distance of not that moving body, the length of the matrix and the imaging time of the two image data and the moving distance, the predicted latency of the matrix and by outputting the predicted waiting time, at the place where the moving body arranged, becomes unnecessary introduction of new equipment, it can be calculated latency in place where moving body lined.

At the entrance of the parking lot, information such as image data is collected from the vehicle 5 passing by the side of the warehousing queue to the information processing server 10 via the network 3 and image analysis is performed. It is not necessary to introduce new equipment, and costs can be reduced. In addition, the present embodiment can be realized with little investment by mounting the in-vehicle information processing apparatus 20 on the vehicle 5 or the like without combining with the information processing server 10 as a system without a new parking lot facility. In addition, since the waiting time is calculated by collecting information from the vehicle 5, the calculation accuracy is improved.

  Also, since information such as image data is collected from the vehicle 5 via the network 3 to the information processing server 10 and analyzed, the waiting time is calculated and stored in the waiting time database 12b of the storage unit 12. Information on the predicted waiting time can be provided for vehicles not lined up in the parking lot.

  Since the waiting time database 12b of the storage unit 12 stores information on the predicted waiting time of various parking lots, the parking lot with the least waiting time can be determined in advance, and the user spends wasted time. There is nothing, and you can select a parking lot.

  In addition, when the past waiting time data is simply used, an error may occur due to various conditions such as weather, gasoline price, and the like. Since information such as image data is collected in the information processing server 10 at any time via the network, the value of the predicted waiting time is less affected by the weather, time zone, etc., and becomes highly accurate. In step S24, since the update time is limited to a predetermined time from the current time, it is possible to provide relatively new information. Become.

Further, with reference to the waiting time database 12b of the storage unit 12 (an example of a prediction latency storage means) reads out the past predicted waiting time in the vicinity of the place where the moving body arranged, based on historical prediction latency read the, When calculating the predicted waiting time of a matrix from the length of the matrix, the imaging time of two image data, and the moving distance, the trend of fluctuations in the predicted waiting time in the past and the currently calculated predicted waiting time can be understood. By correcting the predicted waiting time based on the tendency, the accuracy of the predicted waiting time is improved. For example, as shown in step S <b> 17, the predicted waiting time can be corrected according to the tendency of the amount of change in the waiting time, so that the accuracy of the predicted waiting time is improved.

Further, arranged on the basis of the moving distance of the moving body is in the case of calculating the moving distance of the side-by-side have that moving body, that each moving body that are arranged to move, spacing the moving body (e.g., inter-vehicle distance ) Changes, the movement distance of the entire matrix can be accurately calculated from the average value of each movement distance, and the accuracy of the prediction waiting time is improved.

Further, based on the imaging direction, when calculating the moving distance of the length Oyo BiUtsuri elements of the matrix of moving body, when capturing an image of the matrix from an oblique direction in the image data, the length or the like of the matrix is reduced, based on the imaging direction, it is possible to calculate the actual length, the moving distance of the length Oyo BiUtsuri elements of the matrix can be accurately calculated, thereby improving the accuracy of prediction latency.

As shown in FIG. 13, it obtains image data from the vehicle 6 are arranged in a parking lot as an example of a moving body, and calculates the moving distance of the vehicle 6 itself from these image data, and the calculated The predicted waiting time of the matrix may be calculated based on the moving distance.

  For example, in step S1, the in-vehicle information processing device 20 also acquires image data from the vehicles 6 that are lined up in the parking lot. The in-vehicle information processing apparatus 20 acquires the current position data in step S2, and the vehicle 6 is on the road along the parking lot and is almost stopped. It is determined that In step S6, the in-vehicle information processing apparatus 20 acquires the current time. In step S7, the in-vehicle information processing apparatus 20 receives the image data and the image related information from the vehicles 6 arranged in the parking lot as an information processing server. 10 to send.

  Next, in step S10, the information processing server 10 receives image data and the like, and stores the received image data in the image database 12a of the storage unit 12 in association with the image related information. In step S12, the information processing server 10 refers to the image database 12a in the storage unit 12 and searches for image data having the same vehicle ID and within a predetermined time and within a predetermined time from the imaging time of the acquired image data. .

  Next, the image analysis unit 13 of the information processing server 10 performs image analysis from the acquired image data and the searched image data, and calculates the moving distance of the vehicle 6 itself. For example, the image analysis unit 13 has an object such as a parking lot mark in a landscape captured in image data based on a plurality of image data having different imaging times from the vehicles 6 arranged in the parking lot. The movement distance of the vehicle 6 itself is calculated from the deviation and stored in the storage unit 12. Alternatively, the image analysis unit 13 specifies, for example, a specific vehicle in the matrix from the image data from the vehicle 6 and the image data obtained by imaging the matrix in which the vehicles 6 are arranged from the vehicle 5 as in Step S13. Then, the movement distance is calculated and stored in the storage unit 12. Then, the information processing server 10 calculates the movement distance per time according to the equation (1) and stores it in the storage unit 12.

  The information processing server 10 uses the calculated moving distance of the vehicle 6 itself and the moving distance per time when the image data is transmitted from the traveling vehicle 5 and the predicted waiting time is calculated. For example, the information processing server 10 calculates the travel distance per time calculated based on the image data from the vehicles 6 arranged in the parking lot and the travel distance per time calculated based on the image data from the traveling vehicle 5. Are averaged according to the imaging time, and the moving distance per time is calculated.

Thus, it acquires image data from the transfer moving body is that lined the location lined body (vehicle 6), also calculates the moving distance from these image data, on the basis of the calculated movement distance matrix When calculating the predicted waiting time, the chance of detecting an image increases, and the accuracy in calculating the predicted waiting time is improved.

Note that the in-vehicle information processing apparatus 20 as an example of the information processing terminal may perform the processes of steps S <b> 10 to S <b> 17 of the information processing server 10. This is realized by inter-vehicle communication between vehicles passing near the parking lot. For example, in step S12, image data or the like with different imaging times around the same parking lot is acquired from the vehicle information processing apparatus 20 of another vehicle, image analysis is performed, and a predicted waiting time is calculated. When requesting the output of the predicted waiting time, it requests the in-vehicle information processing device 20 of the vehicle having the predicted waiting time to acquire the predicted waiting time. In this case, for example, serial憶部27 functions as an example of a forecasted waiting time storage means, the control unit 29 functions as an example of the first calculating means. Incidentally, as in the communication unit 11 of the information processing server 10, the communication unit 21, the first obtaining means, and may function as the second acquisition hand stage.

  The car navigation device may have the function of the in-vehicle information processing device 20. Further, instead of the in-vehicle information processing apparatus, a portable terminal such as a portable wireless telephone or a PDA that has a camera or a GPS sensor and can be connected to the information processing server 10 via the network 3 may be used.

If moving body is human, to image the shop or the like are arranged is human the portable terminal transmits the image data and the like to the information processing server 10. When it is desired to know the waiting time of a certain store, the mobile terminal requests the information processing server 10 to acquire and display the predicted waiting time.

1: the information processing system 1a: first acquiring means 1b: second obtaining hand stage
1 e: first calculation hand stage
3: Network 5: vehicles
6: vehicle (moving body)
10: information processing server (information processing apparatus)
11: Communication unit (first acquisition unit, second acquisition hand stage)
12: Storage unit (predicted waiting time storage means)
13: Image analysis unit
14 : Time calculation unit ( first calculation means)
16: Analysis result output section
20 : In-vehicle information processing device (information processing device, information processing terminal)
21: Communication unit (first acquisition unit, second acquisition hand stage)
22: Imaging unit ( first acquisition means)
23: Image detection unit
2 4: current position acquisition unit (second obtaining unit)
25: Time acquisition unit ( second acquisition means)
26: Analysis result output section
2 7: storage unit
2 8: Parking retrieval unit (second acquisition means)
29: Control unit ( first calculation means)

Claims (10)

A first acquisition means for acquiring image data obtained by shooting an image matrix comprising a plurality of mobile,
A second obtaining unit that acquired information about the imaging time 及 beauty imaging location of at least the image data,
(I) the length of the matrix is calculated from the image data, (ii) information and the imaging time of the image pickup location is calculated from the two different images data, of the plurality of mobile 1 of the moving distance of the moving body, a first calculating means for calculating the (iii) wait time of the the imaging time of the two image data, pressurizing et previous SL matrix,
The information processing system characterized by comprising a. The information processing system according to claim 1,
Further comprising a憶means SL you store the calculated wait time by the first calculating means,
The first calculating means, previously with reference to Kiki憶means, past the position of the moving body before Symbol 1 wait read time, while when Chi the past waiting that Desa read, the matrix information processing system and calculates the length, the two imaging time of the image data and the moving distance or al, pre Kimachi Chi time. The information processing system according to claim 1,
A second calculating means for calculating a moving distance of the first moving body from the information on the imaging location and the two image data having different imaging times ;
Said second calculation means, an information processing system, characterized in that based on said plurality of mobile respective travel distance, and calculates the moving distance of the moving body before SL 1. The information processing system according to claim 1,
It said first acquisition means acquires the scene image data landscapes around the captured before Symbol 1 mobile,
The first calculating means, the landscape image capturing location information data, and based on the movement distance of the first moving body image pickup time is calculated from two different of said scene image data, wait time of the matrix Information processing system characterized by calculating The information processing system according to any one of claims 1 to 4,
Further comprising third calculation means for calculating the length of the matrix based on the image data;
The second acquisition means further acquires information regarding the imaging direction of the image data ;
It said third calculating means, based on the imaging direction, calculates the length before Kigyo column,
The information processing system in which the second calculating means, based on the imaging direction, and calculates the moving distance of the moving body before SL 1. In an information processing method of an information processing system for information processing,
A first acquisition step of acquiring image data obtained by image shooting a matrix comprising a plurality of mobile,
A second obtaining step of acquired information about the imaging time 及 beauty imaging location of at least the image data,
(I) the length of the matrix that will be computed from the image data, (ii) information and the imaging time of the image pickup location is calculated from the two different images data, of the plurality of mobile a moving distance of the first moving body, and calculated exit step you calculate the (iii) and the imaging time of the two image data, pressurizing et waiting time before Symbol matrix,
The information processing method characterized by including the. An information processing apparatus included in an information processing system according to any one of claims 1 to 5 and used with an information processing terminal connected via a network,
The first acquisition means;
The second acquisition means;
The first calculating means;
Output means for outputting the waiting time ;
With
The first acquisition means acquires the image data from the information processing terminal;
The second acquisition means acquires from the information processing terminal related information that is at least information regarding the imaging time and imaging location of the image data ,
Those output means, the information processing apparatus characterized by transmitting a pre Kimachi Chi time to the information processing terminal end. An information processing terminal used with the information processing apparatus according to claim 7,
And it transmits the said image data and the previous SL related information to the information processing apparatus,
The information processing terminal characterized by receiving a previous Kimachi Chi time from the information processing apparatus. Computer
First acquisition means for acquiring image data obtained by imaging a matrix composed of a plurality of moving bodies ;
Second acquisition means for acquiring information about an imaging time and imaging locations of at least the image data and,
(I) the length of the image data the matrix that will be calculated from, (ii) the imaging place information, and the imaging time of the is calculated from the two different images data, one of said plurality of mobile a moving distance of the moving body, (iii) a first calculating means for calculating a waiting time of the matrix from the imaging time of the two image data,
Information processing program for causing to function as a.   10. A recording medium on which the information processing program according to claim 9 is recorded so as to be readable by the computer.

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