A surveillance apparatus (100) includes a detection unit (102) processing an image in which an area around a road is captured and detecting that the relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value, and an output unit (104) selecting a type of information to be output, by using an attribute of the person detected to be in the state, and outputting information of the selected type.

TECHNICAL FIELD

The present invention relates to a surveillance system, a surveillance apparatus, a surveillance method, and a program.

BACKGROUND ART

Installation of surveillance cameras in towns has been under way in recent years and is utilized in crime prevention. Patent Document1describes a video surveillance system detecting an act of trespassing on a parking lot or the like by analyzing a video from a security camera and, at the same time, immediately transmitting a warning and the video being the basis of the determination to a display apparatus in a surveillance room where a surveillant stands by, or mobile phones or the like carried by a guard and a person concerned.

RELATED DOCUMENT

Patent Document

DISCLOSURE OF THE INVENTION

Technical Problem

However, the aforementioned document does not disclose a technology for detecting criminal acts committed against a pedestrian and a vehicle, such as kidnapping and vehicle theft.

The present invention has been made in view of the aforementioned circumstances, and an object of the present invention is to provide a technology for detecting situations in which criminal acts committed against a pedestrian and a vehicle may occur.

Solution to Problem

In order to solve the aforementioned problem, aspects of the present invention employ the following configurations, respectively.

A first aspect relates to a surveillance system.

A surveillance system according to the first aspect includes:a plurality of cameras each capturing an image of an area around a road; anda surveillance apparatus surveilling images captured by a plurality of cameras, whereinthe surveillance apparatus includes:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that outputs a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.

A second aspect relates to a surveillance apparatus.

A surveillance apparatus according to the second aspect includes:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that outputs a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.

A third aspect relates to a surveillance method executed by at least one computer.

A surveillance method according to the third aspect includes, by a surveillance apparatus:processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andoutputting a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.

Note that another aspect of the present invention may be a program causing at least one computer to execute the method according to the aforementioned third aspect or a computer-readable storage medium on which such a program is recorded. The storage medium includes a non-transitory tangible medium.

The computer program includes a computer program code causing a computer to implement the surveillance method on the surveillance apparatus when being executed by the computer.

Note that any combination of the components described above and representation of the present invention converted among a method, an apparatus, a system, a storage medium, a computer program, and the like are also valid as embodiments of the present invention.

Further, various components of the present invention do not necessarily need to be individually independent, and, for example, a plurality of components may be formed as a single member, a plurality of members may form a single component, a certain component may be part of another component, and part of a certain component may overlap with part of another component.

Further, while a plurality of procedures are described in a sequential order in the method and the computer program according to the present invention, the order of description does not limit the order in which the plurality of procedures are executed. Therefore, when the method and the computer program according to the present invention are implemented, the order of the plurality of procedures may be changed without affecting the contents.

Furthermore, a plurality of procedures in the method and the computer program according to the present invention are not limited to being individually executed at different timings. Thus, another procedure may occur during execution of any procedure, and an execution timing of any procedure may partially or entirely overlap an execution timing of another procedure.

Advantageous Effects of Invention

The aforementioned aspects can provide a technology for detecting a situation in which a criminal act committed against a pedestrian may occur.

DESCRIPTION OF EMBODIMENTS

Example embodiments of the present invention are described below by using drawings. Note that, in every drawing, similar components are given similar signs, and description thereof is omitted as appropriate.

In the example embodiments, “acquisition” includes at least either of an apparatus getting data or information stored in another apparatus or a storage medium (active acquisition), and an apparatus inputting data or information output from another apparatus to the apparatus (passive acquisition). Examples of the active acquisition include making a request or an inquiry to another apparatus and receiving a response and readout by accessing another apparatus or a storage medium. Further, examples of the passive acquisition include reception of distributed (or, for example, transmitted or push notified) information. Furthermore, “acquisition” may refer to acquisition by selection from received data or information, or selective reception of distributed data or information.

First Example Embodiment

FIG.1is a diagram schematically illustrating an overview of a surveillance system1according to an example embodiment. The surveillance system1is a system in which an image processing apparatus200recognizes a vehicle10and a person20by processing an image captured by a surveillance camera5installed in a town, and a surveillance apparatus100detects criminal acts such as kidnapping and vehicle theft by using the processing result by the image processing apparatus200.

The surveillance system1includes the surveillance apparatus100, the image processing apparatus200, and at least one surveillance camera5. As the surveillance camera5, a camera dedicated to the surveillance system1may be used, or, for example, a previously installed camera may be used.

The surveillance camera5captures an image of a surveilled location and generates an image. The surveillance camera5includes imaging elements such as a lens and a charge coupled device (CCD) image sensor. The surveillance camera5may include a mechanism for performing direction control of the main body of the camera and the lens, zooming control, focusing, and the like following movement of a person entering the angle of view.

The surveillance camera5captures an image of an area including at least a road passable by a vehicle10. For example, the surveillance camera5captures an image of an area including a road with a width wider than that of a vehicle10. Further, the surveillance camera5may capture an image of an area including roads constituted of a sidewalk on which a person20passes and a roadway on which a vehicle10passes. However, without being limited to roads, the surveillance camera5may capture an image of a location where a vehicle10and a person20can enter, such as a parking lot. Note that the surveillance camera5may capture an image of a moving person20or a stationary person20. The surveillance camera5may capture an image of a moving vehicle10or a stationary vehicle10.

The surveillance camera5may capture an image of an area including locations where crimes are likely to occur such as a location behind a structure such as shrubbery, a fence, or a building, an empty location, and a location where crimes have occurred repeatedly in the past.

An image generated by the surveillance camera5is preferably transmitted to the surveillance apparatus100in real time. However, an image transmitted to the surveillance apparatus100may not be immediately transmitted from the surveillance camera5and may be an image delayed by a predetermined time. Images generated by the surveillance camera5may be temporarily stored in a separate storage apparatus and be read from the storage apparatus by the surveillance apparatus100sequentially or at predetermined intervals. Furthermore, images transmitted to the surveillance apparatus100are preferably dynamic images but may be frame images captured at a predetermined intervals or static images.

A method of connecting the surveillance camera5to the surveillance apparatus100may be wireless or wired. In the case of a wireless connection, it is assumed that each of the surveillance camera5and the surveillance apparatus100has a wireless communication function.

For example, the surveillance camera5may be a network camera such as an Internet Protocol (IP) camera.

FIG.2is a functional block diagram illustrating a logical configuration example of the surveillance apparatus100inFIG.1. The surveillance apparatus100includes a detection unit102and an output unit104. The detection unit102detects that the relative distance between a person20and a vehicle10included in an image is in a state of being equal to or less than a reference value (hereinafter also referred to as an approaching state). The output unit104outputs a type of information to be output selected by using an attribute of a person20detected to be in the approaching state.

The state of the relative distance between a person20and a vehicle10being equal to or less than the reference value refers to a state of the distance between the person20and the vehicle10being equal to or less than the reference value. The state of the relative distance between a person20and a vehicle10being equal to or less than the reference value may refer to a state of the relative distance gradually shortening and eventually becoming equal to or less than the reference value by at least either one of the person20and the vehicle10moving, that is, a state of the person20and the vehicle10approaching each other with time. The detection unit102may detect a state of the person20moving and approaching the vehicle10or may detect a state of the vehicle10moving and approaching the person20. The detection unit102may detect a state of both the person20and the vehicle10moving and the vehicle10approaching the moving person20from behind. The detection unit102may detect a state of the vehicle10approaching the moving person20from in front of the person20.

For example, with regard to a change in the relative distance between a person20and a vehicle10, the image processing apparatus200can detect, in a plurality of time-series images, the positions of a feature part of each of the person20and the vehicle10determined in an image and estimate moving directions of the person20and the vehicle10and the relative distance between the person20and the vehicle10from changes in the positions of the person20and the vehicle10and a relative positional relation between the two. The detection unit102detects a state of the relative distance between the person20and the vehicle10included in the image being equal to or less than the reference value, based on the processing result by the image processing apparatus200.

An attribute of a person20is set based on at least one of attributes extracted from an image, such as gender, age, a feature of the face, height, belongings, clothing, and a situation.

Examples of a type of information to be output include information about a type of crime such as a possibility of occurrence of kidnapping and a possibility of occurrence of vehicle theft. An output destination and an output method may vary by the type of information to be output.

Examples of various output destinations that may be considered include a monitor screen for surveillance on a display apparatus at a surveillance center, a terminal (unillustrated) carried by a guard or the like, and a monitor screen for surveillance on a display apparatus (unillustrated) at a police station. Output methods include at least one method out of display on a monitor screen, transmission of an email, and output of a voice or a warning sound from a speaker (unillustrated). At least one of an email address, an IP address of a mobile terminal, and a mobile phone number may be preregistered as an output destination.

As for an output content, a video from a surveillance camera5for which notification is to be given may be output along with information indicating a selected type of information. In a case of a surveillance center, a video from a surveillance camera5for which notification is to be given may be highlighted in a state of videos of a plurality of surveillance cameras5being multi-displayed. For example, multi-display of videos may be switched to single-screen display of only a video from a surveillance camera5for which notification is to be given or display of an enlarged view of the video. Alternatively, a border of a relevant screen in multi-display may be highlighted, or an image to be highlighted may be displayed by superimposition.

In addition to a video from the surveillance camera5, a static image of an image captured by the surveillance camera5, an image (such as an icon or an animation) indicating the type of output information, text information indicating the type of output information, information notifying occurrence of a crime may be displayed. Alternatively, a warning sound based on the type of output information or a voice indicating the type of output information may be output from a speaker at the surveillance center.

Hardware Configuration Example

FIG.3is a block diagram illustrating a hardware configuration of a computer1000providing each of the surveillance apparatus100and the image processing apparatus200in the surveillance system1illustrated inFIG.1.

The computer1000includes a bus1010, a processor1020, a memory1030, a storage device1040, an input-output interface1050, and a network interface1060.

The bus1010is a data transmission channel for the processor1020, the memory1030, the storage device1040, the input-output interface1050, and the network interface1060to transmit and receive data to and from one another. Note that the method of interconnecting the processor1020and other components is not limited to a bus connection.

The processor1020is a processor provided by a central processing unit (CPU), a graphics processing unit (GPU), or the like.

The memory1030is a main storage provided by a random access memory (RAM) or the like.

The storage device1040is an auxiliary storage provided by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read only memory (ROM), or the like. The storage device1040stores program modules implementing the functions of the surveillance apparatus100in the surveillance system1(such as the detection unit102and the output unit104). By reading each program module into the memory1030and executing the program module by the processor1020, each function related to the program module is implemented. Further, the storage device1040also functions as a storage unit storing various types of information used by the surveillance apparatus100.

A program module may be recorded in a storage medium. Storage media recording program modules may include a non-transitory tangible medium usable by the computer1000, and a program code readable by the computer1000(processor1020) may be embedded in the medium.

The input-output interface1050is an interface for connecting the computer1000to various types of input-output equipment.

The network interface1060is an interface for connecting the computer1000to a communication network3. Examples of the communication network3include a local area network (LAN) and a wide area network (WAN). The method of connecting the network interface1060to the communication network3may be a wireless connection or a wired connection. Note that the network interface1060may not be used.

Then, the computer1000is connected to required equipment [such as the surveillance camera5, a display (unillustrated), and a speaker (unillustrated)] through the input-output interface1050or the network interface1060.

The surveillance system1is provided by a combination of the surveillance apparatus100and the image processing apparatus200and therefore is provided by a plurality of computers1000constituting the apparatuses, respectively. For example, the surveillance apparatus100is a server computer. The image processing apparatus200may be an apparatus separate from the surveillance apparatus100, an apparatus included in the surveillance apparatus100, or a combination of the two.

Each component in the surveillance apparatus100according to the present example embodiment inFIG.2is implemented by any combination of hardware and software in the computer1000inFIG.3. Then, it should be understood by a person skilled in the art that various modifications to the implementation method and the apparatus can be made. A block diagram illustrating the surveillance apparatus100according to each example embodiment illustrates a logical function-based block rather than a hardware-based configuration.

FIG.4is a flowchart illustrating an operation example of the surveillance apparatus100according to the present example embodiment. Based on a processing result of a captured image of an area around a road, the detection unit102detects that the relative distance between a person20and a vehicle10included in the image is in a state of being equal to or less than the reference value (Step S103), and the output unit104outputs information of a type selected by using an attribute of the person (Step S107).

According to the present example embodiment, the detection unit102detects a person20and a vehicle10in the approaching state, and the output unit104outputs information selected based on an attribute of the person20. Thus, a situation in which a criminal act committed against a pedestrian or a vehicle, such as kidnapping or vehicle theft, may occur can be detected by using an image from the surveillance camera5capturing an image of an area around a road.

Second Example Embodiment

FIG.5is a functional block diagram illustrating a logical configuration example of the surveillance system inFIG.1. Note that while the image processing apparatus200is provided separately from the surveillance apparatus100, according to the first example embodiment, the present example embodiment is described under the assumption that a surveillance apparatus100also has a function of an image processing apparatus200. Note that it goes without saying that5the surveillance apparatus100and the image processing apparatus200may be hardware-wise separate or the same.

A surveillance system1includes the surveillance apparatus100, a storage apparatus300, and a surveillance camera5.

The surveillance apparatus100outputs information used for surveillance, based on an image generated by the surveillance camera5.

The storage apparatus300stores data required for performing image processing. For example, the storage apparatus300stores information about a feature value for identifying a vehicle10or a person20, and information about a feature value used for determining an attribute of a person.

The surveillance apparatus100includes an acquisition unit120, an object determination unit122, a position determination unit124, an attribute determination unit126, a detection unit102, a selection unit128, and an output unit104.

The acquisition unit120acquires an image generated by the surveillance camera5.

The object determination unit122determines an object by performing image processing on an image acquired by the acquisition unit120. The object determination unit122recognizes and determines a person20and a vehicle10.

By image processing, the position determination unit124determines the positions of a person20and a vehicle10determined by the object determination unit122.

By image processing, the attribute determination unit126determines an attribute of a person20determined by the object determination unit122. The attribute determination unit126determines whether the person20possesses a first attribute or a second attribute.

The first attribute is an attribute being highly likely to lead to a victim of a crime. Examples of the first attribute include “female,” “male,” “child (for example, an estimated age being X years old or younger),” “aged person (for example, an estimated age being Y years old or older),” “girl (such as a female whose estimated age is X years old or younger),” “boy (such as a male whose estimated age is X years old or younger),” “tourist (such as a person carrying a suitcase)”, and “independent action (for example, no other person existing within a predetermined distance).” The first attribute is set based on features extracted from an image, such as gender, age, a feature of the face, height, belongings, clothing, and a situation (where X and Y are integers).

The second attribute is an attribute different from the first attribute. The second attribute includes an attribute having a feature leading to a perpetrator of a criminal act and an attribute of a person other than a person possessing the first attribute, that is, an attribute other than an attribute being highly likely to lead to a victim of a criminal act.

For example, the second attribute may include a person carrying a dangerous object (for example, carrying a long metal bar) and a person covering the face (such as a person wearing a mask). The second attribute is also set based on features extracted from an image, such as gender, age, a feature of the face, height, belongings, clothing, and a situation, similarly to the first attribute.

Note that a person satisfying the first attribute has only to possess an attribute being highly likely to lead to a victim of a crime, and therefore the first attribute is settable according to a criminal situation in a region. For example, “male” may be set to the first attribute in a region where “male” frequently becomes a victim of a crime, and “female” may be set to the first attribute in a region where “female” frequently becomes a victim of a crime.

The detection unit102acquires an attribute related to a person20determined by the object determination unit122and the positions of the person20and a vehicle10.

For each pair of a person20and a vehicle10included in an image, the detection unit102determines whether the relative distance is in a state of being equal to or less than a reference value, that is, an approaching state, based on the positions.

When the detection unit102detects a person20and a vehicle10in the approaching state, the selection unit128acquires an attribute of the person20in the approaching state. The selection unit128selects a type of information to be output, by using the attribute of the detected person20.

The output unit104outputs information of the type selected by the selection unit128.

FIG.6is a flowchart illustrating an operation example of the surveillance system1according to the present example embodiment.

The surveillance apparatus100acquires an image captured by the surveillance camera5and performs image processing (Step S101). Specifically, the object determination unit122recognizes and determines a person20and a vehicle10from the acquired image. Then, the position determination unit124determines the positions of the person20and the vehicle10determined by the object determination unit122.

Next, the detection unit102detects that the relative distance between the person20and the vehicle10included in the image is in a state of being equal to or less than the reference value (Step S103).

When the relative distance between the person20and the vehicle10included in the image is equal to or less than the reference value (YES in Step S103), the attribute determination unit126determines an attribute of the person20determined by the object determination unit122(Step S104). The attribute determination unit126performs image processing on the person20included in the image and determines whether the person20possesses the first attribute or the second attribute.

Note that the timing for determining an attribute of the person20may be before detection of the approaching state of the person20and the vehicle10by the detection unit102.

Then, the selection unit128selects a type of information to be output, based on the attribute of the person20(Step S105).

Then, the output unit104outputs information of the selected type (Step S107).

Note that the output unit104may also output an image or a voice at the detection of the approaching state by the detection unit102or a video captured before and after the detection of the approaching state by the detection unit102.

During a period in which a person20and a vehicle10in the approaching state are not detected by the detection unit102, the processing returns to Step S101and the processing is repeated.

FIG.7is a flowchart illustrating an example of a detailed procedure of Step S105inFIG.6. The attribute determination unit126determines an attribute of the person20detected by the detection unit102(Step S111).

When the attribute determination unit126determines that the person20is a person possessing the first attribute in Step S111, the selection unit128selects a type of information indicating that the person20may fall victim to a crime. For example, the selection unit128selects information indicating that kidnapping of the person20may occur (Step S115).

On the other hand, when the attribute determination unit126determines that the detected person20is a person possessing the second attribute in Step S111, the selection unit128selects a type of information indicating that the person20may commit a crime against the vehicle10. For example, the selection unit128selects information indicating that the person20may commit vehicle theft (Step S117). In other words, the selection unit128may also be considered to select whether the person20may fall victim to a crime or the vehicle10may fall victim to a crime.

The processing returns to Step S107inFIG.6after Step S115and Step S117.

Returning toFIG.6, the output unit104outputs the selected type of information to a predetermined output destination (Step S107). For example, the output unit104may output the selected type of information to a server220at a surveillance center, and the server220at the surveillance center may output information indicating possible occurrence of kidnapping to a monitor screen on a display apparatus equipped in the surveillance center. Furthermore, an image indicating detection of the approaching state may be displayed.

While display on a monitor screen has been exemplified as information output above, any other technique allowing notification of possible occurrence of a crime may be employed.

For example, selected information output by the output unit104may be output by various methods such as voice output, output of a warning sound, transmission of an email to a terminal, and a notification. Further, the output unit104may make a change to a voice or a warning sound, a change to a mail content, or a change to a notified content, based on the information selected.

According to the present example embodiment, the detection unit102detects a person20and a vehicle10in the approaching state, the selection unit128selects a type of crime, based on the attribute of the person20, and the output unit104outputs the selected information. Thus, a situation in which a criminal act committed against a pedestrian or a vehicle, such as kidnapping or vehicle theft, may occur can be detected by using an image from the surveillance camera5capturing an image of an area around a road, and therefore occurrence of a criminal act can be detected. Further, a crime deterrent effect can be expected as surveillance by the surveillance camera5becomes widely known.

Further, when the detection unit102detects the approaching state of a vehicle10and a person20, the output unit104can output information selected based on the attribute of the person20. Thus, even when a vehicle10may fall victim to vehicle theft or the like, a possibility of vehicle theft can be notified before the person20gets into the vehicle10. For example, the output unit104may also output a warning message or a warning sound from a speaker or the like in the neighborhood of the spot. Thus, a crime prevention effect can be improved.

Third Example Embodiment

FIG.8is a functional block diagram illustrating a logical configuration example of the surveillance system inFIG.1. A surveillance system1according to the present example embodiment is similar to those according to the aforementioned example embodiments except for using moving velocity of a vehicle10for determination of a type of information to be output instead of using an attribute of a person20. A surveillance apparatus100according to the present example embodiment includes a moving velocity estimation unit130in place of the attribute determination unit126inFIG.5.

Note that the configuration according to the present example embodiment may be combined with at least one of the configurations according to the other example embodiments without contradicting each other.

The surveillance apparatus100includes an acquisition unit120, an object determination unit122, a position determination unit124, the moving velocity estimation unit130, a detection unit102, a selection unit128, and an output unit104.

The acquisition unit120acquires an image generated by a surveillance camera5.

The object determination unit122determines an object by performing image processing on an image acquired by the acquisition unit120. The object determination unit122recognizes and determines a person20and a vehicle10.

By image processing, the position determination unit124determines the positions of a person20and a vehicle10determined by the object determination unit122.

The moving velocity estimation unit130detects, in a plurality of time-series images, the positions of a feature part of a vehicle10determined by the position determination unit124and estimates moving velocity from a change in the position of the vehicle10. Further, the moving velocity estimation unit130may detect, in a plurality of time-series images, the positions of a feature part of each of a person20and a vehicle10determined in an image and estimate a change in velocity of the vehicle10relative to the person20from a change in a relative positional relation between the person20and the vehicle10. Furthermore, the moving velocity estimation unit130can similarly estimate the moving direction of each of the person20and the vehicle10.

For example, the moving velocity estimation unit130can estimate at what velocity and from which direction a vehicle10approaches a person20or at what velocity and in which direction the vehicle10moves away from the person20.

For example, in a case of kidnapping, a vehicle10approaches a person20from behind at a low speed, puts the person20into the vehicle10, and drives off from the spot. Therefore, when estimating that the moving velocity of a vehicle10is low and determining that the moving direction of the vehicle10is moving in a direction approaching a person20, the moving velocity estimation unit130can determine that kidnapping may occur. Further, in a case of vehicle theft, a person20approaches a stationary vehicle10, and the person20subsequently goes away. Therefore, when estimating that a vehicle10is stationary, the moving velocity estimation unit130can determine that vehicle theft may occur. Note that when the moving velocity of a vehicle10is normal travel velocity, the vehicle10may be determined to be traveling normally.

For each pair of a person20and a vehicle10included in an image, the detection unit102determines whether the pair is in a state of the relative distance being equal to or less than a reference value, that is, an approaching state, based on the positions.

By using the moving velocity of a vehicle10estimated by the moving velocity estimation unit130, the selection unit128selects a type of information to be output. The output unit104outputs information of the type selected by the selection unit128.

FIG.9is a flowchart illustrating an example of operation of the surveillance system1. The flowchart inFIG.9includes Step S101, Step S103, and Step S107in the flowchart inFIG.6and also includes Step S204and Step S205in place of Step S104and Step S105inFIG.6.

The surveillance apparatus100acquires an image captured by the surveillance camera5and performs image processing (Step S101). Specifically, the object determination unit122recognizes and determines a person20and a vehicle10from the acquired image. Then, the position determination unit124determines the positions of the person20and the vehicle10determined by the object determination unit122.

Next, the detection unit102detects that the relative distance between the person20and the vehicle10included in the image is in a state of being equal to or less than the reference value (Step S103).

When the relative distance between the person20and the vehicle10included in the image is equal to or less than the reference value (YES in Step S103), the moving velocity estimation unit130estimates the moving velocity of the vehicle10(Step S204).

Then, the selection unit128selects a type of information to be output, based on the moving velocity of the vehicle10(Step S205).

Then, the output unit104outputs information of the selected type (Step S107).

FIG.10is a flowchart illustrating an example of a detailed procedure of Step S205inFIG.9. The moving velocity estimation unit130determines the moving velocity of the vehicle10(Step S211). When the moving velocity estimation unit130determines that the vehicle10is approaching the person20at a low speed in Step S211, the selection unit128determines that the person20may fall victim to a crime and selects a type of information indicating that the person20may fall victim to a crime as a type of information to be output. For example, the selection unit128selects information indicating that kidnapping of the person20may occur (Step S115). On the other hand, when the moving velocity estimation unit130determines that the vehicle10is stationary in Step S211, the selection unit128determines that the person20may commit a crime and selects a type of information indicating that the person20may commit a crime as a type of information to be output. For example, the selection unit128selects information indicating that the person20may commit vehicle theft (Step S117). The processing returns to Step S107inFIG.9after Step S115and Step S117.

Further, when the moving velocity estimation unit130determines that the moving velocity of the vehicle10indicates neither approaching at a low speed nor stationary in Step S211, the vehicle10may be determined to be merely passing, and therefore the processing returns to Step S107inFIG.9.

Returning toFIG.9, the output unit104outputs information of the selected type (Step S107). When a person20and a vehicle10in the approaching state are not detected (NO in Step S103), the processing returns to Step S101, and the processing is repeated.

According to the present example embodiment, the detection unit102detects a person20and a vehicle10in the approaching state, and the selection unit128determines, by using the moving velocity of the vehicle10, whether the person20may fall victim to a crime or the person20may commit a crime and selects information based on the determination result. Then, the output unit104outputs the selected information. Thus, by using an image from the surveillance camera5capturing an image of an area around a road, a type of criminal act such as kidnapping or vehicle theft can be detected. Further, a crime deterrent effect can be expected due to a wide spread of a fact that surveillance is being performed by the surveillance camera5.

Fourth Example Embodiment

FIG.11is a functional block diagram illustrating a logical configuration example of the surveillance system inFIG.1. A surveillance system1according to the present example embodiment is similar to that according to either of the second example embodiment and the third example embodiment except that a surveillance apparatus100has both the function according to the second example embodiment and the function according to the third example embodiment. The surveillance apparatus100according to the present example embodiment may be combined with at least one of the configurations according to the other example embodiments without contradicting each other.

The surveillance apparatus100includes an acquisition unit120, an object determination unit122, a position determination unit124, an attribute determination unit126, a moving velocity estimation unit130, a detection unit102, a selection unit128, and an output unit104.

The acquisition unit120acquires an image generated by the surveillance camera5.

The object determination unit122determines an object by performing image processing on an image acquired by the acquisition unit120. The object determination unit122recognizes and determines a person20and a vehicle10.

By image processing, the position determination unit124determines the positions of a person20and a vehicle10determined by the object determination unit122.

The attribute determination unit126determines an attribute of a person20by image processing. The attribute determination unit126determines whether the person20possesses a first attribute or a second attribute.

The moving velocity estimation unit130detects, in a plurality of time-series images, the positions of a feature part of a vehicle10determined by the position determination unit124and estimates moving velocity from a change in the position of the vehicle10.

For each pair of a person20and a vehicle10included in an image, the detection unit102determines whether the relative distance is in a state of being equal to or less than a reference value, that is, an approaching state, based on the positions.

The selection unit128selects a type of information to be output, by using the moving velocity of a vehicle10estimated by the moving velocity estimation unit130and an attribute determined by the attribute determination unit126.

The output unit104outputs information of the type selected by the selection unit128.

FIG.12is a flowchart illustrating an example of operation of the surveillance system1. The flowchart inFIG.12includes Step S101, Step S103, Step S104, and Step S107in the flowchart inFIG.6and Step S204inFIG.9and also includes Step S305in place of Step S105inFIG.6or Step S205inFIG.9.

The surveillance apparatus100acquires an image captured by the surveillance camera5and performs image processing (Step S101). Specifically, the object determination unit122recognizes and determines each of a person20and a vehicle10from the acquired image. Then, the position determination unit124determines the positions of the person20and the vehicle10determined by the object determination unit122.

Next, the detection unit102detects that the relative distance between the person20and the vehicle10included in the image is in a state of being equal to or less than the reference value (Step S103).

When the relative distance between the person20and the vehicle10included in the image is equal to or less than the reference value (YES in Step S103), the attribute determination unit126determines an attribute of the person20determined by the object determination unit122(Step S104). Furthermore, the moving velocity estimation unit130detects, in a plurality of time-series images, the positions of a feature part of the vehicle10determined by the position determination unit124and estimates the moving velocity of the vehicle10from a change in the position of the vehicle10(Step S204).

Then, the selection unit128selects a type of information to be output, based on the attribute of the person20and the moving velocity of the vehicle10(Step S305).

Then, the output unit104outputs information of the selected type (Step S107).

FIG.13is a flowchart illustrating an example of a detailed procedure of Step S305inFIG.12. The attribute determination unit126determines an attribute of the person20determined by the object determination unit122(Step S111). In Step S111, the attribute determination unit126determines whether the person20is a person possessing the first attribute and when determining that the person20is a person possessing the first attribute, advances to Step S121. On the other hand, when determining that the person20is a person possessing the second attribute in Step S111, the attribute determination unit126advances to Step S123.

When the moving velocity estimation unit130determines that the vehicle10is approaching the person20at a low speed in Step S121(YES in Step S121), the selection unit128determines that the person20may fall victim to a crime and selects a type of information indicating that the person20may fall victim to a crime as a type of information to be output. For example, the selection unit128selects information indicating that kidnapping of the person20may occur (Step S115). When the moving velocity estimation unit130determines that the vehicle10is not approaching the person20at a low speed (NO in Step S121), the vehicle10may be determined to be merely passing, and therefore the processing returns to Step S107inFIG.12.

When the moving velocity estimation unit130determines that the vehicle10is stationary in Step S123(YES in Step S123), the selection unit128determines that the vehicle10is stationary, determines that the person20may commit a crime, and selects a type of information indicating that the person20may commit a crime as a type of information to be output. For example, the selection unit128selects information indicating that the person20may commit vehicle theft (Step S117). When the moving velocity estimation unit130determines that the vehicle10is not stationary (NO in Step S123), the vehicle10is determined to be merely stopping, and therefore the processing returns to Step S107inFIG.12.

The processing returns to Step S107inFIG.12after Step S115and Step S117.

FIG.14is a flowchart illustrating another example of a detailed procedure of Step S305inFIG.12. The procedure illustrated inFIG.14is the same as the procedure inFIG.13except that a determination using the moving velocity of the vehicle10is made earlier (Step S211) and subsequently a determination using the attribute of the person20is made (Step S131and Step S133).

The selection unit128makes a determination, based on the moving velocity of the vehicle10estimated by the moving velocity estimation unit130(Step S211). When the moving velocity estimation unit130determines that the vehicle10is approaching the person20at a low speed in Step S211, the processing advances to Step S131. When the moving velocity estimation unit130determines that the vehicle10is stationary in Step S211, the processing advances to Step S133. Further, when the moving velocity estimation unit130determines that the moving velocity of the vehicle10indicates neither approaching at a low speed nor stationary in Step S211, the vehicle10may be determined to be merely passing, and therefore the processing returns to Step S107inFIG.12.

When the attribute determination unit126determines that the person20is a person possessing the first attribute in Step S131(YES in Step S131), the selection unit128selects a type of information indicating that the person20may fall victim to a crime as a type of information to be output. For example, the output unit104selects information indicating that kidnapping of the person20may occur (Step S115). When the attribute determination unit126determines that the person20is not a person possessing the first attribute (NO in Step S131), the processing returns to Step S107inFIG.12.

When the attribute determination unit126determines that the person20is a person possessing the second attribute in Step S133(YES in Step S133), the selection unit128determines that the person20may commit a crime and selects a type of information indicating that the person20may commit a crime as a type of information to be output. For example, the selection unit128selects information indicating that the person20may commit vehicle theft (Step S117). When the attribute determination unit126determines that the person20is not a person possessing the second attribute (NO in Step S133), the processing returns to Step S107inFIG.12.

The processing returns to Step S107inFIG.12after Step S115and Step S117.

When the vehicle10is determined to be merely passing or stopping in Step S121or Step S123, or Step S211, Step S131, or Step S133in the flowchart inFIG.13orFIG.14, a type of information to be output is not selected, and therefore the output unit104performs processing without outputting information in Step S107inFIG.12. However, when the vehicle10is determined to be merely passing or stopping in Step S121or Step S123, or Step S211, Step S131, or Step S133in the flowchart inFIG.13orFIG.14, passage or stopping of the vehicle10may be respectively selected as a type of information to be output. In that case, the output unit104may select and output information indicating passage or stopping of the vehicle10in Step S107inFIG.12.

The present example embodiment provides an effect similar to those of the aforementioned example embodiments and can further select a type of information to be output, by using both the moving velocity of a vehicle10and an attribute of a person20, and therefore increases the possibility to more precisely detect a criminal act.

Fifth Example Embodiment

FIG.15is a functional block diagram illustrating a logical configuration example of the surveillance system inFIG.1. A surveillance system1according to the present example embodiment is the same as that according to the second example embodiment except for selecting a type of information to be output, based on whether a person20is taking an independent action. In addition to the configuration according to the second example embodiment inFIG.5, a surveillance apparatus100according to the present example embodiment further includes a head count determination unit132. Note that the surveillance apparatus100according to the present example embodiment may be combined with at least one of the configurations according to the other example embodiments without contradicting each other.

The surveillance apparatus100includes an acquisition unit120, an object determination unit122, a position determination unit124, an attribute determination unit126, the head count determination unit132, a detection unit102, a selection unit128, and an output unit104.

The acquisition unit120acquires an image generated by a surveillance camera5.

The object determination unit122determines an object by performing image processing on an image acquired by the acquisition unit120. The object determination unit122recognizes and determines a person20and a vehicle10.

The position determination unit124determines the positions of a person20and a vehicle10determined by the object determination unit122.

The attribute determination unit126determines an attribute of a person20by image processing. The attribute determination unit126determines whether the person20possesses a first attribute or a second attribute.

The head count determination unit132determines the number of persons20. For example, the head count determination unit132determines whether a plurality of persons20are determined by the object determination unit122. When the object determination unit122determines a plurality of persons20, the head count determination unit132determines whether persons the distance between whom is equal to or less than a reference value exist among the persons20. For example, the head count determination unit132determines whether persons the distance between whom is equal to or less than the reference value exist among a plurality of persons20, based on the positions of the persons20determined by the position determination unit124. Note that the reference value may be the same value as a reference value for determining the relative distance between a vehicle10and a person20or may be a different value.

When persons the distance between whom is equal to or less than the reference value exist among the plurality of persons20, the head count determination unit132determines that the persons do not take independent actions. The head count determination unit132determines that an independent action is being taken when a plurality of persons20do not exist or persons the distance between whom is equal to or less than the reference value do not exist among a plurality of persons20.

The reason is that kidnapping is likely to occur particularly when a person is alone. Note that an independent action may involve not only a single person but also a small number of persons such as two or three persons.

For each pair of a person20and a vehicle10included in an image, the detection unit102determines whether the relative distance is in a state of being equal to or less than a reference value, that is, an approaching state, based on the positions.

The selection unit128selects a type of information to be output depending on whether a determination result made by the head count determination unit132indicates that a person20is taking an independent action.

The output unit104outputs information of the type selected by the selection unit128.

FIG.16is a flowchart illustrating an example of operation of the surveillance system1. The flowchart inFIG.16includes Step S141in place of Step S121in the flowchart inFIG.13. However, the flowchart inFIG.16may include Step S121inFIG.13. The order of Step S121and Step S141is not particularly limited.

The attribute determination unit126determines an attribute of the person20determined by the object determination unit122(Step S111). When determining that the person20possesses the first attribute in Step S111, the attribute determination unit126advances to Step S141. On the other hand, when determining that the person20possesses the second attribute in Step S111, the attribute determination unit126advances to Step S123.

When the head count determination unit132determines that the person20is taking an independent action in Step S141(YES in Step S141), the selection unit128selects a type of information indicating that the person20may fall victim to a crime as a type of information to be output. For example, the output unit104selects information indicating that kidnapping of the person20may occur (Step S115). When the head count determination unit132determines that the person20is not taking an independent action (NO in Step S141), the vehicle10may be determined to be merely passing, and therefore the processing returns to Step S107inFIG.12.

Processing in and after Step S123is the same as that inFIG.13, and therefore description thereof is not repeated.

FIG.17is a flowchart illustrating another example of operation of the surveillance system1. The flowchart inFIG.17is the same as that inFIG.16except that the order of Step S111and Step S141is reversed in the flowchart inFIG.16. The flowchart inFIG.17may include Step S121inFIG.13. In that case, the order of Step S121and Step S141is not particularly limited.

The head count determination unit132determines whether the person20is taking an independent action (Step S141). When the head count determination unit132determines that the person20is taking an independent action in Step S141(YES in Step S141), the processing advances to to Step S111. When the head count determination unit132determines that the person20is not taking an independent action in Step S141(NO in Step S141), the vehicle10is determined to be merely passing, and therefore the processing returns to Step S107inFIG.12.

In Step S111, the attribute determination unit126determines an attribute of the person20determined by the object determination unit122. When the attribute determination unit126determines that the person20possesses the first attribute in Step S111, the processing advances to Step S115. On the other hand, when the attribute determination unit126determines that the person20possesses the second attribute in Step S111, the processing advances to Step S123. Processing from here onward is the same as that inFIG.16, and therefore description thereof is not repeated.

The present example embodiment enables determination of whether a person20is taking an independent action by the head count determination unit132and when the person20is taking an independent action, enables output that kidnapping is highly likely to occur. By combination with another condition, determination precision can be further improved and frequent notification can be prevented.

Sixth Example Embodiment

A surveillance system1according to the present example embodiment differs from that according to the aforementioned fourth example embodiment in being configured to detect that a vehicle10is in a stationary state and that entry and exit of a person20are performed after the vehicle becomes stationary and to select a type of information to be output by using the result.

Specifically, operation of a detection unit102and operation of a selection unit128are different. The surveillance system1is described below by using the functional block diagram according to the fourth example embodiment inFIG.11. Note that a surveillance apparatus100according to the present example embodiment may be combined with at least one of the configurations according to the other example embodiments without contradicting each other.

For each pair of a person20and a vehicle10included in an image, the detection unit102determines whether the relative distance is in a state of being equal to or less than a reference value, that is, an approaching state, based on the positions. Further, when determining that a vehicle10determined to be in the approaching state by the detection unit102is in the stationary state from moving velocity estimated by the moving velocity estimation unit130, the detection unit102further detects whether entry and exit of a person into and from the vehicle10are made.

The selection unit128selects a type of information to be output, by further using a detection result of entry and exit of a person by the detection unit102.

For example, as illustrated inFIG.18, in a case of kidnapping, a vehicle10may approach a person20(inFIG.18Ato inFIG.18B), grab the person20by extending only an arm from the vehicle10, drag the person20into the vehicle10, and take the person20away (inFIG.018C). In other words, a person does not come out of the stationary vehicle10in the case of kidnapping. In a case of vehicle theft, a driver is highly likely to come out of a stationary vehicle10. By detecting the situations, kidnapping and vehicle theft are discriminated.

FIG.19is a flowchart illustrating an example of operation of the surveillance system1. The flowchart inFIG.19includes Step S211, Step S131, Step S133, Step S115, and Step S117in the flowchart inFIG.14and further includes Step S151.

In Step S211, when the moving velocity estimation unit130estimates that the vehicle10is moving at a low speed and the detection unit102determines that the vehicle10is approaching the person20, the process advances to Step S131, and the attribute determination unit126determines an attribute of the person20.

Next, when determining that the vehicle10is stationary in Step S211, the moving velocity estimation unit130advances to Step S151. In Step S151, the detection unit102determines whether a person, that is, a driver comes out of the stationary vehicle10. For example, the detection unit102may detect entry and exit of a person by determining whether a person comes out of the vehicle10within a predetermined time from the determination that the vehicle is in the stationary state by the moving velocity estimation unit130.

When the detection unit102detects that a person does not come out of the vehicle10within the predetermined time (NO in Step S151), the possibility of kidnapping is high, and therefore the processing advances to Step S131. Further, when the moving velocity estimation unit130determines that the moving velocity of the vehicle10indicates neither approaching at a low speed nor stationary in Step S211, the vehicle10may be determined to be merely passing, and therefore the processing returns to Step S107inFIG.12. Processing in and after Step S131is the same as that according to the aforementioned example embodiments, and therefore description thereof is not repeated.

On the other hand, when the detection unit102detects a person coming out of the vehicle10(YES in Step S151), the attribute determination unit126determines an attribute of the person20in the approaching state (Step S133). Then, when the attribute determination unit126determines that the person possesses the second attribute (YES in Step S133), the selection unit128selects information indicating that the person20may commit vehicle theft, similarly toFIG.14(Step S117).

The present example embodiment enables selection of a type of information to be processed by detecting whether a person comes out of a stationary vehicle10. Accordingly, determination precision can be further improved.

While the example embodiments of the present invention have been described above with reference to the drawings, the example embodiments are exemplifications of the present invention, and various configurations other than those described above may be employed.

For example, since detection of a criminal act is performed by using an image from the surveillance camera5, an image at detection of the criminal act can be recorded, and the record can be used as evidence at occurrence of a crime. The above can lead to early resolution of a case, arrest of a culprit, and rescue of a victim.

Furthermore, the detection unit102may perform processing by using an image from a specific surveillance camera5out of a plurality of surveillance cameras5each capturing an image of an area around a road. As described above, surveillance may be performed by using an image from a surveillance camera5installed at a particularly unsafe location, a location where criminal acts such as kidnapping and vehicle theft frequently occur, or the like. Further, priority may be given to a specific surveillance camera5, and the proportion of surveillance time of the high-priority surveillance camera5may be set longer than that of another surveillance camera5.

Furthermore, the detection unit102may acquire and store a facial image of a person20, the relative distance between a vehicle10and the person20being detected to be in a state of being equal to or less than a reference value. The facial image may be stored in the memory1030or the storage device1040inFIG.3, or the like.

As illustrated inFIG.20, in a case of vehicle theft, an owner30of a stationary vehicle10first comes out of the vehicle10(inFIG.20A). The detection unit102detects a person coming out of the vehicle10and acquires and temporarily stores a facial image of the person A (the owner of the vehicle10) coming out of the vehicle10.

Further continuing the surveillance, the detection unit102detects a person20approaching the vehicle10(inFIG.20B). At this time, the detection unit102acquires a facial image of the person20. Then, the detection unit102may transmit the facial image of the person A acquired earlier and the facial image of the person20acquired later to the image processing apparatus200and cause the image processing apparatus200to check whether the two are the same person. The selection unit128selects a type of information to be output, by using the check result. When the two are not the same person, it is determined to be the vehicle theft (inFIG.20C). When the two are the same person, it is determined to be the owner.

Further, in a case of a facial image not being able to be captured, the person20approaching the vehicle10inFIG.20Bmay be determined to commit vehicle theft when the person20comes out of the vehicle10immediately (after a predetermined time) after once getting into the vehicle10.

Furthermore, a procedure other than the example of detecting entry and exit of a person into and from a stationary vehicle10and using the result thereof as described inFIG.19according to the fifth example embodiment may be considered.FIG.21is a flowchart illustrating an example of operation of the surveillance system1. The flowchart inFIG.21includes Step S151in place of Step S131in the flowchart inFIG.14. In this example, when the detection unit102determines that the vehicle10is approaching the person20at a low speed in Step S211, the processing advances to Step S151, and whether a person comes out of the vehicle10is determined. When the detection unit102does not detect a person coming out (NO in Step S151), the possibility of kidnapping is high, and therefore the processing advances to Step S115. When the detection unit102detects a person coming out (YES in Step S151), the vehicle10is determined to be merely stopping, and therefore the processing returns to Step S107inFIG.12. The remaining processing is the same as that inFIG.14, and therefore description thereof is not repeated.

While the present invention has been described with reference to example embodiments (and examples) thereof, the present invention is not limited to the aforementioned example embodiments (and examples). Various changes and modifications that may be understood by a person skilled in the art may be made to the configurations and details of the present invention without departing from the scope of the present invention.

Note that when information about a user is acquired and/or used in the present invention, the acquisition and/or use is assumed to be performed legally.

Examples of reference embodiments are added as supplementary notes below.1. A surveillance apparatus including:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that selects a type of information to be output, by using an attribute of the person detected to be in the state, and outputting the selected type of information.2. The surveillance apparatus according to 1., whereinthe output unit selects the type of information to be output, by further using moving velocity of the vehicle detected to be in the state.3. A surveillance apparatus including:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; and an output unit that selects a type of information to be output, by using moving velocity of the vehicle detected to be in the state, and outputs the selected type of information.4. The surveillance apparatus according to any one of 1. to 3., whereinthe output unit selects the type of information to be output, further depending on whether the person detected to be in the state takes an independent action.5. The surveillance apparatus according to any one of 1. to 4., whereinthe detection unit detects that the vehicle detected to be in the state is determined to be in a stationary state, and that entry and exit of a person are performed after the vehicle becomes stationary, andthe output unit selects the type of information to be output by further using a detection result made by the detection unit.6. The surveillance apparatus according to any one of 1. to 5., whereinthe detection unit performs the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.7. A surveillance system including:a plurality of cameras each capturing an image of an area around a road; anda surveillance apparatus surveilling images captured by a plurality of cameras, whereinthe surveillance apparatus includes:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that selects a type of information to be output, by using an attribute of the person detected to be in the state, and outputs the selected type of information.8. The surveillance system according to7., whereinthe output unit in the surveillance apparatus selects the type of information to be output, by further using moving velocity of the vehicle detected to be in the state.9. A surveillance system including:a plurality of cameras each capturing an image of an area around a road; anda surveillance apparatus surveilling images captured by a plurality of cameras, whereinthe surveillance apparatus includes:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that selects a type of information to be output, by using moving velocity of the vehicle detected to be in the state, and outputs the selected type of information.10. The surveillance system according to any one of 7. to 9., whereinthe output unit in the surveillance apparatus selects the type of information to be output, further depending on whether the person detected to be in the state takes an independent action.11. The surveillance system according to any one of 7. to 10., wherein,the detection unit in the surveillance apparatus detects that the vehicle detected to be in the state is determined to be in a stationary state, and that entry and exit of a person are performed after the vehicle becomes stationary, andthe output unit in the surveillance apparatus selects the type of information to be output, by further using a detection result made by the detection unit.12. The surveillance system according to any one of 7. to 11., whereinthe detection unit in the surveillance apparatus performs the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.13. A surveillance method including, by a surveillance apparatus:processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andselecting a type of information to be output, by using an attribute of the person detected to be in the state, and outputting the selected type of information.4. The surveillance method according to 13., further including, by the surveillance apparatus,selecting the type of information to be output, by further using moving velocity of the vehicle detected to be in the state.15. A surveillance method including, by a surveillance apparatus:processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andselecting a type of information to be output, by using moving velocity of the vehicle detected to be in the state, and outputting the selected type of information.16. The surveillance method according to any one of 13. to 15., further including, by the surveillance apparatus,selecting the type of information to be output, further depending on whether the person detected to be in the state takes an independent action.17. The surveillance method according to any one of 13. to 16., further including, by the surveillance apparatus:detecting that the vehicle detected to be in the state is in a stationary state, and that entry and exit of a person are performed after the vehicle becomes stationary; andselecting the type of information to be output, by further using the detection result.18. The surveillance method according to any one of 13. to 17., further including, by the surveillance apparatus,performing the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.19. A program for causing a computer to execute:a procedure for processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; anda procedure for selecting a type of information to be output, by using an attribute of the person detected to be in the state, and outputting the selected type of information.20. The program according to 19., further causing a computer to executea procedure for selecting the type of information to be output, by further using moving velocity of the vehicle detected to be in the state.21. A program for causing a computer to execute:a procedure for processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; anda procedure for selecting a type of information to be output, by using moving velocity of the vehicle detected to be in the state, and outputting the selected type of information.22. The program according to any one of 19. to 21., further causing a computer to executea procedure for selecting the type of information to be output, further depending on whether the person detected to be in the state takes an independent action.23. The program according to any one of 19. to 22., further causing a computer to execute:a procedure for detecting that the vehicle detected to be in the state is determined to be in a stationary state, and that entry and exit of a person are performed after the vehicle becomes stationary; anda procedure for selecting the type of information to be output, by further using a detection result made by the procedure for detection.24. The program according to any one of 19. to 23., further causing a computer to execute a procedure for performing the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.

More examples of reference embodiments are added as supplementary notes below.25. A surveillance apparatus including:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that outputs a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.26. The surveillance apparatus according to 25., further including:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and determining a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;an attribute determination unit that, by performing the image processing, determines an attribute of the person determined by the position determination unit; anda selection unit that, when the detection unit detects a person and a vehicle in the state, selects the type of information to be output, by using the determined attribute of the detected person, whereinthe output unit outputs information of the type selected by the selection unit.

27. The surveillance apparatus according to 25. or 26., further including:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and determines a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;a moving velocity estimation unit that estimates moving velocity of the vehicle determined by the position determination unit, from a change in a position of the vehicle; anda selection unit that selects the type of information to be output, by using the moving velocity of the vehicle estimated by the moving velocity estimation unit, whereinthe output unit outputs information of the type selected by the selection unit.28. The surveillance apparatus according to any one of 25. to 27., further including:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and determines a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;a headcount determination unit that determines the number of the persons determined by the object determination unit and determines whether the determined person takes an independent action; anda selection unit that selects a type of the information to be output selected based on a determination result made by the headcount determination unit, whereinthe output unit outputs information of the type selected by the selection unit.29. The surveillance apparatus according to 27. or 28. citing 27., wherein,when determining that the vehicle detected to be in the state is in a stationary state from the moving velocity estimated by the moving velocity estimation unit, the detection unit further detects whether entry and exit of a person into and from the vehicle are performed,the selection unit selects a type of the information to be output, by further using a detection result of the entry and exit of the person made by the detection unit, andthe output unit outputs information of the type selected by the selection unit.30. The surveillance apparatus according to any one of 25. To 29., whereinthe detection unit performs the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.31. A surveillance system including:a plurality of cameras each capturing an image of an area around a road; anda surveillance apparatus surveilling images captured by a plurality of cameras, whereinthe surveillance apparatus includes:a detection unit that processes an image in which an area around a road is captured and detects that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andan output unit that outputs a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.32. The surveillance system according to 31., whereinthe surveillance apparatus further includes:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and detects a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;an attribute determination unit that, by performing the image processing, determines an attribute of the person determined by the position determination unit; anda selection unit that, when the detection unit detects a person and a vehicle in the state, selects the type of information to be output, by using the determined attribute of the detected person, whereinthe output unit in the surveillance apparatus outputs information of the type selected by the selection unit.33. The surveillance system according to 31. or 32., whereinthe surveillance apparatus further includes:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and determines a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;a moving velocity estimation unit that estimates moving velocity of the vehicle determined by the position determination unit, from a change in a position of the vehicle; anda selection unit that selects the type of information to be output, by using the moving velocity of the vehicle estimated by a moving velocity estimation unit, whereinthe output unit in the surveillance apparatus outputs information of the type selected by the selection unit.34. The surveillance system according to any one of 31. to 33., further including:an acquisition unit that acquires the image in which the area around the road is captured, the image being generated by a camera;an object determination unit that recognizes and determines a person and a vehicle by performing image processing on the image acquired by the acquisition unit;a position determination unit that, by performing the image processing, determines positions of the person and the vehicle determined by the object determination unit;a headcount determination unit that determines the number of the persons determined by the object determination unit and determines whether the determined person takes an independent action; anda selection unit that selects a type of the information to be output selected based on a determination result made by the headcount determination unit, whereinthe output unit in the surveillance apparatus outputs information of the type selected by the selection unit.35. The surveillance system according to 33. or 34. citing 33., wherein,when determining that the vehicle detected to be in the state is in a stationary state from the moving velocity estimated by the moving velocity estimation unit, the detection unit in the surveillance apparatus further detects whether entry and exit of a person into and from the vehicle are performed,the selection unit in the surveillance apparatus selects a type of the information to be output, by further using a detection result of the entry and exit of the person by the detection unit, andthe output unit in the surveillance apparatus outputs information of the type selected by the selection unit.36. The surveillance system according to any one of 31. to 35., whereinthe detection unit in the surveillance apparatus performs the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.37. A surveillance method including, by a surveillance apparatus:processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; andoutputting a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.38. The surveillance method according to 37., further including, by a surveillance apparatus:acquiring the image in which the area around the road is captured, the image being generated by a camera;recognizing and determining a person and a vehicle by performing image processing on the acquired image;determining positions of the determined person and the determined vehicle by performing the image processing;determining an attribute of the determined person by performing the image processing;when detecting a person and a vehicle in the state, selecting the type of information to be output, by using the determined attribute of the detected person; andoutputting information of the selected type.39. The surveillance method according to 37. or 38., further including, by the surveillance apparatus:acquiring the image in which the area around the road is captured, the image being generated by a camera;recognizing and determining a person and a vehicle by performing image processing on the acquired image;determining positions of the determined person and the determined vehicle by performing the image processing;estimating moving velocity of the determined vehicle from a change in a position of the vehicle;selecting the type of information to be output, by using the moving velocity of the estimated vehicle; andoutputting information of the selected type.40. The surveillance method according to any one of 37. to 39., further including, by the surveillance apparatus:acquiring the image in which the area around the road is captured, the image being generated by a camera;recognizing and determining a person and a vehicle by performing image processing on the acquired image;determining positions of the determined person and the determined vehicle by performing the image processing;determining the number of the determined persons and determining whether the determined person takes an independent action;selecting a type of the information to be output selected based on a result of the determination; andoutputting information of the selected type.41. The surveillance method according to 39. and claim 40. citing 39., further including, by the surveillance apparatus:when determining that the vehicle detected to be in the state is in a stationary state from the estimated moving velocity, further detecting whether entry and exit of a person into and from the vehicle are performed;selecting a type of the information to be output, by further using a detection result of the entry and exit of the person; andoutputting information of the selected type.42. The surveillance method according to any one of 37. to 41., further including, by the surveillance apparatus:performing the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.43. A program for causing a computer to execute:a procedure for processing an image in which an area around a road is captured and detecting that a relative distance between a person and a vehicle included in the image is in a state of being equal to or less than a reference value; anda procedure for outputting a type of information to be output, the type of information being selected by using an attribute of the person detected to be in the state.44. The program according to 43., further causing a computer to execute:a procedure for acquiring the image in which the area around the road is captured, the image being generated by a camera;a procedure for recognizing and determining a person and a vehicle by performing image processing on the image acquired in the procedure for acquisition;a procedure for, by performing the image processing, determining positions of the person and the vehicle determined in the procedure for determining a person and a vehicle;a procedure for, by performing the image processing, determining an attribute of the person determined in the procedure for determining positions;a procedure for, when a person and a vehicle in the state are detected in the procedure for detection, selecting the type of information to be output, by using the determined attribute of the detected person; anda procedure for outputting information of the type selected in the procedure for selection.45. The program according to 43. or 44., further causing a computer to execute:a procedure for acquiring the image in which the area around the road is captured, the image being generated by a camera;a procedure for recognizing and determining a person and a vehicle by performing image processing on the image acquired in the procedure for acquisition;a procedure for, by performing the image processing, determining positions of the person and the vehicle determined in the procedure for determining a person and a vehicle;a procedure for estimating moving velocity of the vehicle determined in the procedure for determining positions, from a change in a position of the vehicle;a procedure for selecting the type of information to be output, by using the moving velocity of the vehicle estimated in the procedure for estimating moving velocity; anda procedure for outputting information of the type selected in a procedure for selection.46. The program according to any one of 43. to 45., further causing a computer to execute:a procedure for acquiring the image in which the area around the road is captured, the image being generated by a camera;a procedure for recognizing and determining a person and a vehicle by performing image processing on the image acquired in the procedure for acquisition;a procedure for, by performing the image processing, determining positions of the person and the vehicle determined in the procedure for determining a person and a vehicle;a procedure for determining the number of the persons determined in the procedure for determining a person and a vehicle and determining whether the determined person takes an independent action;a procedure for selecting a type of the information to be output selected based on a result of the determination; anda procedure for outputting information of the type selected in the procedure for selection.47. The program according to 45. or 46. citing 45., further causing a computer to executea procedure for, when the vehicle detected to be in the state is determined to be in a stationary state from the moving velocity estimated in the procedure for estimating moving velocity, further detecting whether entry and exit of a person into and from the vehicle are performed,selecting a type of the information to be output, by further using a detection result of the entry and exit of the person, andoutputting information of the selected type.48. The program according to any one of 43. to 47., further causing a computer to executea procedure for performing the processing by using an image from a specific camera out of a plurality of cameras each capturing an image of the area around the road.

This application is based upon and claims the benefit of priority from International Application No. PCT/JP2020/001760, filed on Jan. 20, 2020, the disclosure of which is incorporated herein in its entirety by reference.

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