JP7302088B1 - system and program - Google Patents

Abstract

An object of the present invention is to improve the accuracy of detecting a stagnation of people from images captured by a camera. A system as an example of the present disclosure is a system for analyzing video captured by a camera, detecting an object in the video, measuring the residence time of the object, measuring the moving speed of the object, When the residence time of the target is equal to or greater than the first threshold and the moving speed of the target is equal to or greater than the second threshold, it is detected that the target is staying, and an output indicating that the target is staying is output. [Selection drawing] Fig. 2

Description

The present disclosure relates to systems and programs.

2. Description of the Related Art Conventionally, there is known a technique of analyzing an image captured by a camera and detecting a person in the image. With such a technique, for example, when a person stays in a predetermined area continuously for a predetermined time or longer, an alarm is output to notify that effect.

JP 2021-72475 A

However, if the presence of people is detected based only on the time spent in a predetermined area, the accuracy of detection tends to decrease when the presence of people is difficult to detect, such as at night.

Therefore, one of the problems to be solved by the present disclosure is to provide a system and a program capable of improving the accuracy of detecting people's stagnation from images captured by cameras.

An example system of the present disclosure is a system that analyzes video captured by a camera, detects a target in the video, measures the dwell time of the target, measures the moving speed of the target, measures the dwell time of the target, is greater than or equal to the first threshold and the moving speed of the target is greater than or equal to the second threshold, it is detected that the target is staying, and an output indicating that the target is staying is provided.

In addition, a system as another example of the present disclosure is a system that analyzes video captured by a camera, detects a target in the video, measures the residence time of the target, measures the moving speed of the target, When the moving speed of the object exceeds the threshold, it is detected that the object is staying, and an output indicating the staying of the object is performed, and the threshold changes so as to decrease as the staying time of the object increases.

Further, a system as still another example of the present disclosure is a system that analyzes video captured by a camera, detects a target in the video, measures the residence time of the target, and measures the moving speed of the target. , when the residence time of the object exceeds the threshold, it detects that the object is staying and outputs an output indicating that the object is staying. .

Yet another exemplary method of the present disclosure is a method performed by a system for analyzing video captured by a camera, comprising detecting an object in the video and measuring dwell time of the object. and measuring the moving speed of the target, detecting that the target is staying when the target staying time is equal to or greater than the first threshold and the target moving speed is equal to or greater than the second threshold, and providing an output indicating dwell of the object.

Yet another exemplary method of the present disclosure is a method performed by a system for analyzing video captured by a camera, comprising detecting an object in the video and measuring dwell time of the object. and measuring the moving speed of the target, detecting that the target is staying when the moving speed of the target is equal to or higher than the threshold value, and outputting an output indicating the staying of the target, The threshold changes so that it becomes smaller as the residence time of the object increases.

Yet another exemplary method of the present disclosure is a method performed by a system for analyzing video captured by a camera, comprising detecting an object in the video and measuring dwell time of the object. and measuring the movement speed of the target, detecting that the target is staying when the target staying time is equal to or greater than the threshold, and outputting an output indicating the staying of the target, The threshold changes so that it becomes smaller as the movement speed of the target increases.

In addition, a program as still another example of the present disclosure causes a computer that configures a system for analyzing video captured by a camera to detect a target in the video, measure the dwell time of the target, and measuring the moving speed of the target, and detecting that the target is staying when the target staying time is equal to or greater than the first threshold and the target moving speed is equal to or greater than the second threshold, and the target staying It is a program for outputting and executing.

In addition, a program as still another example of the present disclosure causes a computer that configures a system for analyzing video captured by a camera to detect a target in the video, measure the dwell time of the target, and , detecting that the object is staying when the moving speed of the object exceeds a threshold value, and outputting an output indicating that the object is staying. , and the threshold changes so as to decrease as the residence time of the object increases.

In addition, a program as still another example of the present disclosure causes a computer that configures a system for analyzing video captured by a camera to detect a target in the video, measure the dwell time of the target, and , detecting that the object is staying when the staying time of the object is equal to or greater than a threshold value, and outputting an output indicating the staying of the object. , and the threshold changes so as to decrease as the movement speed of the object increases.

FIG. 1 is an exemplary and schematic block diagram showing the functional configuration of the system according to the embodiment. FIG. 2 is an exemplary and schematic sequence diagram showing the flow of processing executed in the system according to the embodiment; FIG. 3 is an exemplary and schematic diagram for explaining sensitivity setting as an example of condition setting according to the embodiment. FIG. 4 is an exemplary and schematic diagram for explaining area setting as an example of condition setting according to the embodiment. FIG. 5 is an exemplary and schematic diagram for explaining notification setting as an example of condition setting according to the embodiment. FIG. 6A is an exemplary schematic diagram for explaining an example of logic used in detection processing according to the embodiment. FIG. 6B is an exemplary schematic diagram for explaining an example of logic used in detection processing according to the embodiment. FIG. 7 is an exemplary schematic diagram for explaining another example of logic used in the detection process according to the embodiment; FIG. 8 is an exemplary schematic diagram showing another example of the display mode of the timeline according to the embodiment; FIG. 9 is an exemplary and schematic diagram showing an example of a form of notification using e-mail according to the embodiment. 10 is an exemplary and schematic block diagram showing the hardware configuration of the camera, cloud platform, and information processing apparatus included in the user terminal according to the embodiment; FIG.

Hereinafter, embodiments and modifications of the present disclosure will be described based on the drawings. The configurations of the embodiments and modifications described below, as well as the actions and effects brought about by the configurations, are merely examples, and are not limited to the following description.

FIG. 1 is an exemplary and schematic block diagram showing the functional configuration of a system 100 according to an embodiment.

As shown in FIG. 1 , system 100 according to an embodiment includes camera 110 , cloud platform 120 and user terminal 130 .

The camera 110 includes an imaging unit 111, a detection unit 112, and a communication unit 113 as functional modules. The cloud platform 120 also includes a communication unit 121, a recording unit 122, and an image information generation unit 123 as functional modules. Further, the user terminal 130 includes an input reception unit 131, a communication unit 132, and a display/playback unit 133 as functional modules.

Camera 110 is installed, for example, in a store, and is communicably connected to cloud platform 120 via a network. Also, the cloud platform 120 is communicably connected to the user terminal 130 via a network. Accordingly, images captured by the camera 110 (and information detected based on the images) can be provided to the user terminal 130 via the cloud platform 120 .

Here, by analyzing the image captured by the camera 110, it is possible to detect the person appearing in the image. As such a technique, there is conventionally known a technique of outputting an alarm to notify that when a person stays in a predetermined area of a video continuously for a predetermined time or longer.

However, if the presence of people is detected based only on the length of time they stayed within the predetermined area, the accuracy of detection tends to decrease when it is difficult to detect the presence of people, such as at night.

Therefore, in the embodiment, it is possible to improve the accuracy of detecting the presence of people from the image captured by the camera 110 by the configuration and processing described below.

FIG. 2 is an exemplary and schematic sequence diagram showing the flow of processing executed in the system 100 according to the embodiment. Note that the cloud platform 120 is simply represented as the cloud 120 in FIG. 2 for the sake of simplification.

First, setting processing for setting various conditions for the camera 110 using the user terminal 130 will be described. Although the details will be described later, the conditions include, for example, what standard (sensitivity) is used to detect people, which area in the photographing range of the camera 110 is to be used for human detection, and how people are detected. It is a condition regarding how to notify the fact that it has been done.

In the setting process, first, in step S201, the input reception unit 131 of the user terminal 130 sets conditions based on user operations via a UI (user interface) as shown in FIGS. 3 to 5 below. accept.

FIG. 3 is an exemplary and schematic diagram for explaining sensitivity setting as an example of condition setting according to the embodiment.

An image 300 illustrated in FIG. 3 is an example of a UI that receives user operations for performing various settings. In the image 300, the user sets the criteria (sensitivity) to be used for human detection by setting each item in the area 320 displayed on the right side according to the selection of the setting button 310 on the left side. It can be performed. An area 320 includes an interface 321 for switching on/off whether or not to detect a person, and LOW, MIDDLE, and HIGH (LOW<MIDDLE<HIGH sensitivity in the order of LOW<MIDDLE<HIGH) to set the sensitivity for detecting a person. an interface 322 for selecting from among three levels (i.e., more sensitive detection of people), and an interface 323 for setting the target area for human detection. . Here, when one of the sensitivities (LOW, MIDDLE, HIGH) is selected, the threshold for the dwell time of the person and the threshold for the moving speed of the person are set accordingly. These thresholds may be fixed values as described later with reference to FIG. In that case, the higher the sensitivity, the lower each threshold should be. Also, as will be described later with reference to FIG. 7, it may be a variable value. In that case, the higher the sensitivity, the steeper the slope of the curve that indicates the variable value, or the lower the minimum threshold for the movement speed of people and the minimum threshold for the dwell time of people, which serve as the reference. . Although this drawing shows a state in which HIGH is selected as the default, the default may be LOW or MIDDLE, or may be selectable by the user. Moreover, the threshold for the residence time of a person and the threshold for the movement speed of a person are not limited to the setting via the sensitivity as described above, and may be directly set by the user. When the user operates the interface 323, an image 400 as shown in FIG. 4 is output.

FIG. 4 is an exemplary and schematic diagram for explaining area setting as an example of condition setting according to the embodiment.

An image 401 shown in FIG. 4 is an example of a UI that receives a user's operation related to area setting.

In this image 401, on the left side, a list of areas 402 in which already set area names are described is displayed, along with information indicating the upper limit of the number of areas that can be set and the number of areas that are currently set, and a new area. A new creation button 403 for registering is displayed. In each area 402, the colored icon on the left side is associated with the color of the area set in the image 400 displayed in area 401A. A desired color can be set for each area. Also, by clicking the delete button on the right side of each area 402, it is possible to delete the corresponding area. When one of the areas 402 is clicked to select it, both its name and the corresponding area within the image 400 displayed in area 401A are highlighted, making it identifiable as being selected. By clicking/dragging the corresponding area in the image 400 while the area is selected, the position and shape of the area can be changed.

For example, in the example shown in FIG. 4, there are six areas 411 to 416 as set areas. After clicking the new creation button 403, the user can set an area having a desired position, size, and shape by performing a drag-and-drop operation on the image 400 displayed in the area 401A. be. For example, by sequentially clicking the vertices of the area and double-clicking the last vertex, it is possible to set an area connecting those vertices.

It should be noted that the manner in which the notification that a person is detected in the area set as described above is to be set is set using the UI shown in FIG. 5 below.

FIG. 5 is an exemplary and schematic diagram for explaining notification setting as an example of condition setting according to the embodiment.

An image 300 illustrated in FIG. 5 is an example of a UI that receives user operations for performing various settings. The user can use areas 350, 360, and 370 displayed on the right side of the image 300 in accordance with the selection of the notification button 340 on the left side to decide how to notify that a person has been detected. Settings can be made. An area 350 is for setting and confirming in a schedule format whether or not notification by e-mail or push notification for each item such as "motion", "sound", "connection/disconnection", and "human detection" is performed on each day of the week. possible interface. An area 360 displays an interface for switching ON/OFF of whether to notify by email and ON/OFF of whether to notify by push notification. An area 370 displays an interface for switching ON/OFF whether or not to notify that a person has been detected. By using area 350 and using areas 360 and 370, the user can specify whether or not to be notified that a person has been detected each day of the week, and whether to send such notification by e-mail or by push notification. It is possible to set

Returning to FIG. 2, after setting the conditions in step S201, the communication unit 132 of the user terminal 130 transmits the set conditions to the cloud platform 120 in step S202. Then, the communication unit 121 of the cloud platform 120 receives the conditions transmitted by the user terminal 130 .

Then, in step S<b>203 , the communication unit 121 of the cloud platform 120 transfers the conditions received from the user terminal 130 to the camera 110 . The communication unit 113 of the camera 110 then receives the conditions transmitted by the cloud platform 120 .

Then, in step S204, the detection unit 112 of the camera 110 saves the conditions received from the cloud platform 120 for use in the imaging process described below. Thus, the setting process ends.

Next, a description will be given of a photographing process including photographing of an image by the camera 110 and detection of various information based on the image.

In the shooting process, first, in step S211, the shooting unit 111 of the camera 110 shoots an image. Then, in step S212, the detection unit 112 of the camera 110 executes detection processing for detecting a person from the image based on the setting performed in the setting processing described above. The sensing process is performed, for example, by logic as shown in FIGS. 6A and 6B or FIG. 7 below.

FIG. 6A is an exemplary schematic diagram for explaining an example of logic used in detection processing according to the embodiment.

In the example shown in FIG. 6A, a curve L601 shows an example of temporal transition of the detected moving speed of a person. The horizontal axis corresponds to the elapsed time (residence time) after the person was detected, and the vertical axis corresponds to the moving speed of the detected person.

Here, in the embodiment, two indicators, ie, the residence time of a person and the speed of movement of a person, are taken into consideration when detecting the stay of a person. Therefore, in the example shown in FIG. 6A, not only the threshold (first threshold) t _thresh regarding the residence time of people but also the threshold (second threshold) V _thresh regarding the moving speed of people are provided.

That is, in the embodiment, _{the presence of a person is not detected only when the residence time of a person exceeds the threshold value t thresh .} When it becomes (refer to point P601 shown in FIG. 6A), stagnation of people is detected. As a result, it is possible to improve the accuracy of detection of the presence of people, for example, as compared with the case where the presence of people is detected by considering only the dwell time of people.

FIG. 6B is an exemplary schematic diagram for explaining an example of logic used in detection processing according to the embodiment. FIG. 6B is for re-explaining the above logic explained using FIG. 6A based on another example.

That is, in the example shown in FIG. 6B, the curve L602 shows an example of the temporal transition of the moving speed of the detected person. The horizontal axis corresponds to the elapsed time (residence time) after the person was detected, and the vertical axis corresponds to the moving speed of the detected person.

Here, the logic shown in FIG. 6B is similar to the logic shown in FIG. 6A. Therefore, in the example shown in FIG. 6B, a person's stay is detected at a point P602 where the person's stay time is equal to or greater than the threshold t _thresh and the person's moving speed is equal to or greater than the threshold V _thresh .

Note that the two thresholds described above may be set separately from each other according to a user's instruction, or the two thresholds may be integrally set. In the latter case, for example, a configuration is adopted in which a plurality of combinations of two thresholds are set in advance, and one combination is determined from among the plurality of combinations according to the sensitivity set by the user. sell.

By the way, in the above description, the case where the threshold for the staying time and the threshold for the moving speed are fixed is exemplified. However, in the embodiment, as shown in FIG. They may change in conjunction with each other.

FIG. 7 is an exemplary schematic diagram for explaining another example of logic used in the detection process according to the embodiment;

In the example shown in FIG. 7, curves L701 and L702 show an example of the time transition of the moving speeds of two people. The horizontal axis corresponds to the elapsed time (residence time) after the person was detected, and the vertical axis corresponds to the moving speed of the detected person.

Here, in the example shown in FIG. 7, the threshold for the residence time and the threshold for the moving speed change in conjunction with each other as indicated by the curve L700. That is, in the example shown in FIG. 7, the threshold value of the residence time is set so as to decrease as the moving speed increases. Alternatively, the moving speed threshold is set so as to decrease as the residence time increases. Note that the moving speed threshold is set to a value at least greater than V _{thresh_min} . If such a curve L700 is represented by a formula, for example, the movement speed threshold V _thresh =(predetermined parameter a/residence time t)+V _{thresh_min} . Note that instead of the moving speed threshold, the dwell time threshold may be set to a value at least greater than T _{thresh_min} . If such a curve L700 is represented by a formula, for example, the threshold for the residence time T _thresh =(predetermined parameter b/moving speed v)+T _{thresh_min} .

As a result, in the example shown in FIG. 7, the presence of people is detected at points P701 and P702 where both the dwell time and moving speed of people exceed the curve L700. In general, even if the residence time is short, if the movement speed is high, there is a high possibility that the target is a person. According to the shown logic, it is possible to accurately detect the stagnation of people.

Returning to FIG. 2, when step S212 ends, the communication unit 113 of the camera 110 transmits the image captured in step S211 and the result of the detection processing in step S212 to the cloud platform 120 in step S213. Here, the image is associated with the time when the image was taken, and the detection result includes at least the time when the presence of people was detected by the detection logic described above. Note that the detection result may be transmitted only when the condition set in step S201 is satisfied, or may be transmitted at other times. The communication unit 121 of the cloud platform 120 then receives the information transmitted by the camera 110 .

Then, in step S<b>214 , the recording unit 122 of the cloud platform 120 records the video and the detection result received from the camera 110 . Then, in step S215, the image information generation unit 123 of the cloud platform 120 generates image information called a timeline as shown in FIG. Thus, the photographing process ends.

FIG. 8 is an exemplary schematic diagram showing an example of a display mode of a timeline according to the embodiment;

Image 800 shown in FIG. 8 is an example of a UI including a timeline generated by cloud platform 120 . This UI can be provided to the user terminal 130 as information indicating the detection result of the presence of people in the confirmation process to be described later.

Image 800 shown in FIG. 8 includes area 801 in which a timeline is displayed. This timeline shows, in chronological order, the timings of images that meet the various conditions set in the above-described setting process, such as when a person's stay is detected by the above detection logic, in an identifiable manner in chronological order. be. The term identifiable as used herein means, for example, a mode in which an object such as a colored band or flag is added to the timing that satisfies the above conditions on the timeline and displayed. When coloring, the color may correspond to the same color as the color set in the above-described area setting (see FIG. 4). In FIG. 8, the case where a person's stay is detected is classified as an event of "human detection", and with a color distinguishable from other events "sound", "motion", "snapshot", and "intrusion detection", A colored band appears on the timeline. Then, when the user designates a desired time from among them, the image corresponding to that time is displayed at the top. By providing such a timeline to the user terminal 130, it becomes possible to appropriately narrow down the timings to which attention should be paid in the video.

In addition, in the embodiment, the format for outputting the information indicating the detection result of the presence of people is not limited to the above format such as the timeline. For example, in the embodiment, a time-series list of thumbnails showing images of timings at which people's stay was detected may be output as information indicating the result of people's stay detection.

Returning to FIG. 2, confirmation processing for confirming the image captured and the information detected in the above-described image capture processing will be described.

In the confirmation process, first, in step S221, the input reception unit 131 of the user terminal 130 receives a confirmation request based on the user's operation for confirming the image captured and the information detected in the above-described imaging process.

Then, in step S<b>222 , the communication unit 132 of the user terminal 130 transmits the received confirmation request to the cloud platform 120 . The communication unit 121 of the cloud platform 120 then receives the confirmation request transmitted by the user terminal 130 .

In step S<b>223 , the image information generation unit 223 of the cloud platform 120 reads the image information (timeline) generated in the above-described shooting process in response to the confirmation request received from the user terminal 130 .

Then, in step S224, the communication unit 121 of the cloud platform 120 transmits the image information read out in step S223 to the user terminal 130. FIG. The communication unit 132 of the user terminal 130 then receives the image information transmitted by the cloud platform 120 .

Then, in step S225, the display/playback unit 133 of the user terminal 130 displays the image information received from the cloud platform 120 on a display (not shown). The image information is displayed, for example, in the form shown in FIG. 8 described above.

Then, in step S226, the input reception unit 131 of the user terminal 130 receives a selection instruction as an operation for selecting (designating) a video image at a desired timing based on the image information described above. Specifically, the specification of the time on the timeline in FIG. 8 described above corresponds to the selection instruction.

Then, in step S<b>227 , the communication unit 132 of the user terminal 130 transmits the received selection instruction to the cloud platform 120 . The communication unit 121 of the cloud platform 120 then receives the selection instruction transmitted by the user terminal 130 .

Then, in step S<b>228 , the image information generation unit 223 of the cloud platform 120 reads the video recorded in the above-described shooting process according to the selection instruction received from the user terminal 130 . That is, the video at the time corresponding to the one selected (designated) in step S226 is read.

Then, in step S229, the communication unit 121 of the cloud platform 120 transmits the video read out in step S228 to the user terminal . The communication unit 132 of the user terminal 130 then receives the video transmitted by the cloud platform 120 .

Then, in step S230, the display/playback unit 133 of the user terminal 130 plays back the video received from the cloud platform 120 on a display (not shown). Thus, the confirmation process ends.

In addition, in the embodiment, the user is automatically notified of the detection result of the presence of people not only in response to the confirmation request manually made by the user, but also according to the notification conditions set in step S221. It is possible. Such automatic notification is performed, for example, by sending an e-mail as shown in FIG. 9 below to the user terminal. Further, such automatic notification may be performed, for example, by outputting a push notification via an OS or an application for video confirmation on the user terminal while the user is using the OS or the like.

FIG. 9 is an exemplary and schematic diagram showing an example of a form of notification using e-mail according to the embodiment.

An image 900 shown in FIG. 9 is an example of a UI displayed in an e-mail when the result of detection of people staying is notified by e-mail. The user can check the image at the timing when the stay of a person is detected by the image displayed in the area 910 provided in the upper part of the image 900, and the image displayed in the area 910 provided in the lower part of the image 900 From the contents displayed in , it is possible to confirm which device installed in which area the stagnation of people was detected.

As explained above, the system 100 according to the embodiment analyzes the video captured by the camera 110 . The system 100 detects an object (for example, a person) in an image, measures the residence time of the object, and measures the moving speed of the object. The system 100 detects that the target is staying when the target staying time is equal to or greater than the first threshold and the target moving speed is equal to or greater than the second threshold, and an output indicating the target staying (for example notification). According to such a configuration, when it is difficult to detect the presence of people, such as at night, the accuracy of detection of the presence of people is higher than when detecting the presence of people by considering only the dwell time of people. can be improved.

In addition, in the embodiment, a plurality of combinations of the first threshold and the second threshold can be set in advance. In this case, the system 100 sets the sensitivity of detection of target retention according to the user's instruction, and according to the sensitivity, from among the plurality of combinations, the first to be used for detection of target retention A combination of the threshold and the second threshold may be determined. According to such a configuration, two thresholds, the first threshold and the second threshold, can be easily set using one index of sensitivity.

Also, in an embodiment, the system 100 can separately set the first threshold and the second threshold according to a user's instruction. According to such a configuration, by separately setting the first threshold and the second threshold, it is possible to finely set the criteria for detecting the stay of the object.

Also, in the embodiment, the second threshold may decrease as the residence time of the target increases, and the first threshold may decrease as the moving speed of the target increases. In general, even if the residence time is short, if the moving speed is high, there is a high possibility that the target should be detected. Since there is a high possibility that there is a stagnation, according to such a configuration, the stagnation of the target can be detected with high accuracy.

Also, in an embodiment, the system 100 sets an area for detecting an object. According to such a configuration, it is possible to detect an object by narrowing down to a set area instead of the entire area shown in the image, so that the load of processing for detecting an object can be reduced.

Furthermore, in the embodiment, the system 100 outputs an output indicating the stay of the object to display the timing of detecting the stay of the object in a timeline so that it can be identified (see FIG. 8). According to such a configuration, it is possible to notify the user of the timing at which the retention of the object is detected in a visually easy-to-understand manner.

In addition, in the system 100 according to the embodiment, the output indicating the stay of the target includes notifying by e-mail that the stay of the target has been detected (see FIG. 9). According to such a configuration, it is possible to easily notify the user of the detection of the retention of the object by using an e-mail.

Finally, hardware configurations included in the camera 110, the cloud platform 120, and the user terminal 130 that configure the system 100 according to the above-described embodiment will be described. In the embodiment, the camera 110, the cloud platform 120, and the user terminal 130 are configured to include an information processing device (computer) 1100 having the hardware configuration shown in FIG. 10 below, for example.

FIG. 10 is an exemplary and schematic block diagram showing the hardware configuration of the camera 110, the cloud platform 120, and the information processing device 1100 included in the user terminal 130 according to the embodiment.

Note that FIG. 10 shows only the hardware configuration substantially common among the camera 110, the cloud platform 120, and the user terminal 130. As shown in FIG. Therefore, it should be noted that the actual hardware configurations of the camera 110, the cloud platform 120, and the user terminal 130 differ in various ways other than those shown in FIG.

As shown in FIG. 10, the information processing device 1000 includes a processor 1010, a memory 1020, a storage 1030, an input/output interface (I/F) 1040, and a communication interface (I/F) 1050. there is These hardware are connected to bus 1060 .

Processor 1010 is configured as, for example, a CPU (Central Processing Unit), and controls the operation of each unit of information processing apparatus 1000 in a centralized manner.

Memory 1020 includes, for example, ROM (Read Only Memory) and RAM (Random Access Memory), volatile or non-volatile storage of various data such as programs executed by processor 1010, and processor 1010 executing programs. We will realize the provision of a work area for

Storage 1030 includes, for example, HDD (Hard Disk Drive) or SSD (Solid State Drive), and stores various data in a non-volatile manner.

The input/output interface 1040 inputs data from an input device (not shown) such as a keyboard and mouse to the information processing apparatus 1000 and outputs data from the information processing apparatus 1000 to an output device (not shown) such as a display and a speaker. ) to control the output of data to

Communication interface 1050 allows information processing device 1000 to communicate with other devices.

Each functional module (see FIG. 1) of the camera 110, the cloud platform 120, and the user terminal 130 according to the embodiment is an information processing program prestored in the memory 1020 or the storage 1030 by the processor 1010 of each information processing device 1000. is implemented as a group of functional modules through the cooperation of hardware and software. However, in the embodiment, part or all of the functional module group shown in FIG. 1 may be realized only by hardware such as a specially designed circuit.

Note that the information processing program described above does not necessarily have to be pre-stored in memory 1020 or storage 1030 . For example, the information processing program described above can be installed in a computer-readable medium such as various magnetic disks such as a flexible disk (FD), or various optical disks such as a DVD (Digital Versatile Disk). It may also be provided as a computer program product coded in an executable form.

Further, the information processing program described above may be provided or distributed via a network such as the Internet. That is, the information processing program described above may be provided in a form of being stored on a computer connected to a network such as the Internet, and being downloaded via the network.

Although the embodiments of the present disclosure have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are included in the scope of the invention described in the claims and their equivalents.

100 system 110 camera 111 imaging unit 112 detection unit 113 communication unit 120 cloud platform 121 communication unit 122 recording unit 123 image information generation unit 130 user terminal 131 input reception unit 132 communication unit 133 display reproduction unit

Claims (17)

A system for analyzing video captured by a camera,
detecting an object in the image;
measuring the residence time of the target;
measuring the moving speed of the target;
When the residence time of the target is greater than or equal to a first threshold and the moving speed of the target is greater than or equal to a second threshold, an output indicating that the target has been detected is performed.
system. A plurality of combinations of the first threshold and the second threshold are set in advance,
setting the sensitivity of detection of the object according to a user's instruction;
Determining one combination of the first threshold and the second threshold to be used from among the plurality of combinations according to the sensitivity;
The system of claim 1. Setting the first threshold and the second threshold separately according to a user's instruction;
The system of claim 1. The second threshold changes so as to decrease as the residence time of the target increases.
The system of claim 1. The first threshold changes so as to decrease as the movement speed of the target increases.
The system of claim 1. A system for analyzing video captured by a camera,
detecting an object in the image;
measuring the residence time of the target;
measuring the moving speed of the target;
When the movement speed of the target is equal to or greater than a threshold, outputting an output indicating that the target has been detected ,
The threshold changes so as to decrease as the residence time of the target increases.
system. A system for analyzing video captured by a camera,
detecting an object in the image;
measuring the residence time of the target;
measuring the moving speed of the target;
When the residence time of the target is equal to or greater than a threshold, outputting an output indicating that the target has been detected ,
The threshold changes so as to decrease as the moving speed of the target increases.
system. setting an area for detecting the target;
System according to any one of claims 1-7. The output is to display the timing at which the target is detected in an identifiable manner on a timeline.
System according to any one of claims 1-7. the output is to notify by email that the object has been detected ;
System according to any one of claims 1-7. The output is to display an image of the timing when the target is detected as a thumbnail,
System according to any one of claims 1-7. A method performed by a system for analyzing video captured by a camera, comprising:
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
performing an output indicating that the target has been detected when the residence time of the target is equal to or greater than a first threshold and the moving speed of the target is equal to or greater than a second threshold;
A method, including A method performed by a system for analyzing video captured by a camera, comprising:
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
outputting an output indicating that the target has been detected when the moving speed of the target is greater than or equal to a threshold;
including
The threshold changes so as to decrease as the residence time of the target increases.
Method. A method performed by a system for analyzing video captured by a camera, comprising:
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
When the residence time of the target is equal to or greater than a threshold, outputting an output indicating that the target has been detected ;
including
The threshold changes so as to decrease as the moving speed of the target increases.
Method. The computer that makes up the system that analyzes the video taken by the camera,
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
performing an output indicating that the target has been detected when the residence time of the target is equal to or greater than a first threshold and the moving speed of the target is equal to or greater than a second threshold;
A program to run the The computer that makes up the system that analyzes the video taken by the camera,
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
outputting an output indicating that the target has been detected when the moving speed of the target is greater than or equal to a threshold;
A program for executing
The threshold changes so as to decrease as the residence time of the target increases.
program. The computer that makes up the system that analyzes the video taken by the camera,
detecting an object in the video;
measuring the residence time of the object;
measuring the moving speed of the object;
When the residence time of the target is equal to or greater than a threshold, outputting an output indicating that the target has been detected ;
A program for executing
The threshold changes so as to decrease as the moving speed of the target increases.
program.

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