JP6405606B2 - Image processing apparatus, image processing method, and image processing program - Google Patents

Description

  The present invention relates to a technique for confirming an object that matches a specified attribute from objects (people, vehicles, etc.) captured in a video image.

  Conventionally, surveillance cameras are installed in various places such as airports, stations, shopping centers, street corners and the like. In addition, the person who is being picked up is a person to be detected, and the face of the person captured in the captured image of the surveillance camera is compared with the face of the person to be detected, and the person to be detected is captured. It has been proposed to detect a captured image (see Patent Document 1).

  In addition, in this type of device, when a detection target person being imaged is detected, a notification of detection including the location where the captured image was captured, the date and time, the detection target person being imaged, etc. is notified to the related organizations. Is also going.

  In related organizations and the like, security guards or the like search for a detection target person based on the notified detection notification.

Japanese Patent Laid-Open No. 2004-62560

  However, troubles such as some incidents and accidents may occur outside the imaging area of the surveillance camera. In such a case, since the surveillance camera is not imaging the site, the captured images of the plurality of surveillance cameras installed around the site where the trouble has occurred are confirmed, and a person who seems to be a party is found.

  Since the apparatus proposed in the above-mentioned Patent Document 1 is based on the premise that the face of the person to be detected is already known, the detection target whose face is not known for the captured image of the surveillance camera Person (participant of the trouble that has occurred) cannot be easily searched. Therefore, the person in charge, such as a security guard, listened to the person who witnessed the trouble (witness) and heard the characteristics of the party's appearance (masked, wearing sunglasses, etc.) and visually observed the image captured by the surveillance camera. I was looking for a person that seems to be the party being imaged. As described above, it takes time and effort to confirm a person whose face is not known even if the appearance characteristics are known from the captured image of the surveillance camera.

  An object of the present invention is to provide a technique for easily confirming a corresponding object captured in a video image if it is an object such as a person or a vehicle whose characteristics concerning appearance are known.

  In order to achieve the above object, the image processing apparatus of the present invention is configured as follows.

The attribute determination unit processes the frame image related to the video image input to the image input unit, and for the imaged object, the attribute related to the appearance of the predetermined object and the attribute related to the state of the object To determine whether it is true. The video image input to the image input unit may be a real-time image of an imaging area captured by an imaging device such as a surveillance camera, or may be an image recorded on a medium. Further, the attribute determination unit determines, as an attribute related to the state of the object, at least whether the moving speed of the object is faster than other objects. Attribute determination unit is based on the average moving speed of the object on the frame image, whether the moving speed of the object is fast in comparison with other objects, rather than on real space, the average moving speed of the object on the frame image Judgment on the basis of .

  The type of object for which the attribute determining unit determines the attribute is, for example, a moving object such as a person or a vehicle.

Also, it attributes other than the moving speed you determine whether the attribute determining unit is held true may be determined according to the type of the object of interest. For example, if the target object type is a person, whether it is wearing a mask, wearing sunglasses, or other attributes related to appearance, whether it is moving so that the face is not imaged (the face is What is necessary is just to define the attribute concerning states (movement state), such as whether it is moving so that it may hide. If the target object type is a vehicle, whether the license plate is hidden so that it will not be imaged, whether the license plate number written on the license plate is hidden (the license plate itself is not hidden) .), Appearance attributes such as whether the driver's face is hidden from the front side of the vehicle, whether it is running backwards, whether it is meandering, whether it is running without light, etc. What is necessary is just to define the attribute concerning a state (movement state).

  The output image generation unit generates an output image in which the object determined to be applicable by the attribute determination unit is distinguished from other objects for the attribute of the object received by the attribute designation reception unit. For example, with respect to the attributes of the object received in the attribute designation receiving unit, the attribute determining unit may be configured to display thumbnail images for displaying a list of images of the objects determined to be applicable by the attribute determining unit, or attributes of the object received in the attribute designation receiving unit. A highlighted display image that displays an image of an object that has been determined to be true more than other images is generated as an output image. Then, the output unit outputs the output image generated by the output image generation unit.

  A person in charge such as a security guard can easily confirm a person captured in a video image captured by a surveillance camera or the like. For example, even for a person whose face is not known, it is possible to narrow down by the attribute relating to the appearance that is known and the attribute relating to the state. In addition, confirmation of other types of objects such as a vehicle captured in a video image captured by a surveillance camera or the like can also be narrowed down based on the attributes relating to the appearance and the attributes relating to the state.

  Therefore, in the case of an object such as a person or a vehicle whose appearance characteristics are known, the time and labor required to confirm the corresponding object captured in the video image can be reduced.

  The image processing apparatus according to the present invention provides, for each object captured in the video image input to the image input unit, an image of the object and a plurality of types of attributes predetermined by the attribute determination unit. It is good also as a structure provided with the attribute determination result memory | storage part which matches and memorize | stores the determination result determined whether it applies to an attribute.

  If comprised in this way, the process in an attribute determination part can be performed in advance with respect to the object currently imaged by the video image input into the image input part. As a result, when the attribute designation accepting unit accepts the specification of the attribute of the object, the output image generating unit can immediately start generating the output image, and the processing efficiency can be improved.

  The image processing apparatus according to the present invention captures an object in a video image input to the video image input unit when any object included in the output image output from the output unit is selected and designated. It is good also as a structure provided with the reproducing part which reproduces | regenerates the position which exists.

  With this configuration, it is possible to easily confirm a video image in which an object narrowed down by attributes is captured.

  According to the present invention, if an object such as a person or a vehicle whose features relating to appearance are known, the corresponding object captured in the video image can be easily confirmed.

It is a block diagram which shows the structure of the principal part of an image processing apparatus. It is a figure which shows attribute determination result DB. It is a flowchart which shows the attribute determination result DB creation process in an image processing apparatus. It is a flowchart which shows an attribute determination process. It is a flowchart which shows the determination processing of attributes other than moving speed. It is a flowchart which shows an output image generation process. It is a figure which shows the example of a display screen of the thumbnail image which is an output image. It is a flowchart which shows a reproduction | regeneration process.

  Hereinafter, an image processing apparatus according to an embodiment of the present invention will be described.

  FIG. 1 is a block diagram showing the configuration of the main part of the image processing apparatus according to this example. The image processing apparatus 1 according to this example includes a control unit 2, an image input unit 3, an image processing processor 4, an attribute determination result database 5 (attribute determination result DB 5), an operation unit 6, an output unit 7, It has. The image processing apparatus 1 according to this example determines, for each of a plurality of predetermined attributes, whether a person is captured in a video image, and determines an output image using the determination result. Generate and output.

  The control unit 2 controls the operation of each part of the main body of the image processing apparatus 1.

  A video image (moving image) is input to the image input unit 3. This video image may be a real-time image of an imaging area captured by an imaging device (not shown) such as a surveillance camera, or a video image recorded on a medium such as a hard disk (a moving image compressed by MPEG2 or the like) Image data).

  The image processor 4 has a configuration corresponding to the attribute determination unit referred to in the present invention, processes a video image input to the image input unit 3, and sets a plurality of predetermined attributes for a person being imaged. Then, it is determined whether or not the attribute is applicable. In this example, two appearance attributes are defined: whether a mask is worn or whether sunglasses are worn. Further, two attributes are defined as whether the movement speed is fast or whether the face is moving so as not to be imaged.

  Although details will be described later, the image processor 4 cuts out the face of the person captured in the input video image, and determines whether the face is applicable to the appearance attribute. Further, the image processor 4 tracks a person who is captured in the input video image, and determines whether or not the attribute of the state (moving state) is applicable.

  The image processor 4 has a configuration corresponding to the output image generation unit referred to in the present invention, and generates an output image based on the determination result for the above-described attributes.

The image processor 4 corresponds to a computer that executes the image processing method according to the present invention (executes an image processing program).

  The attribute determination result DB 5 determines in advance an ID for identifying a person captured in the input video image, a face image of the person (a face image cut out from a frame image in which the person is captured), and the like. This is a database in which the determination results determined for a plurality of types of attributes and the playback start position of the input video image (time data indicating the position where the person is captured in the video image) are registered in association with each other. FIG. 2 is a diagram showing the configuration of this attribute determination result DB. In FIG. 2, “◯” indicates that the corresponding attribute is applicable, and “X” indicates that the corresponding attribute is not applicable. In addition, for a person who applies to face concealment (person with ID 0006 shown in FIG. 2), it is not necessary to register a face image, but in this example, an image is registered so that the body can be confirmed. . The attribute determination result DB 5 has a configuration corresponding to the attribute determination result storage unit referred to in the present invention.

  The operation unit 6 has an input device such as a mouse and a keyboard, and accepts an input operation by an operator on the image processing apparatus 1 main body. The operator uses the operation unit 6 to perform an input operation related to designation of an object attribute type, which will be described later. The image processor 4 has a configuration corresponding to the attribute designation accepting unit referred to in the present invention, and accepts the attribute type of the object designated by the input operation performed by the operator in the operation unit 6.

  The output unit 7 outputs the output image generated by the image processor 4 and the video image (reproduced image) input to the image input unit 3. A display device (not shown) is connected to the output unit 7. This display device displays the image output by the output unit 7.

  Hereinafter, the operation of the image processing apparatus 1 will be described. The image processing apparatus 1 executes an attribute determination result DB creation process, an output image generation process, a reproduction process, and the like described below.

  FIG. 3 is a flowchart showing attribute determination result DB creation processing in the image processing apparatus. In the image processing apparatus 1, a frame image related to a video image input to the image input unit 3 is processed in time series by an image processor 4.

  The image processor 4 detects an object imaged in the processing target frame image (s1). In this example, the object to be detected is a person. For the detection of an object, for example, an object having a human-like shape is detected as a person by pattern matching for each moving body detected by an inter-frame difference image or a background difference image.

  The image processor 4 detects each person detected in s1 by associating a frame number for identifying a frame image to be processed, a captured image of the person cut out from the frame image, and a position (coordinate) on the frame image. A record is created (s2).

  The image processor 4 determines whether or not each person who has created a detection record in s2 is a detected person who has been captured in the previous frame image to be processed (s3). In s3, the image processor 4 is the person who has not been imaged in the previous processing target frame image (that is, the imaging timing of the previous processing target frame image, the imaging timing of the current processing target frame image, If it is determined that it is a person appearing between, an ID is given to the person (s4). Further, the image processor 4 creates an object map of the person associated with the ID assigned in s4 (s5). In s5, an object map in which the detection record created in s2 is registered is created using the ID assigned in s4. This object map is created separately for each person who is given an ID.

  If the image processor 4 determines that the person has been detected in s3, the image processor 4 determines the ID already assigned to the person (s6). Further, the image processor 4 updates the object map for additionally registering the detection record created in s2 to the object map associated with the ID determined in s6 (s7).

  As described above, the processing related to s3 to s7 is performed for each person who created the detection record in s2.

  The image processor 4 extracts a person (detected person) who has been captured in the previous frame image to be processed but not captured in the current frame image to be processed (s8).

The image processor 4 performs an attribute determination process for determining the attribute of each person extracted in s8 (s9). In s9, for each person extracted in s8,
(1) Whether you have a mask,
(2) Whether wearing sunglasses (3) Whether moving speed is fast,
(4) Whether the face is moving so that it is not imaged,
It is determined whether or not these four attributes are true.

  Details of the attribute determination processing according to s9 will be described later. Further, the attribute determination processing according to s9 may be separated from the other processing shown in FIG. 3 and executed in parallel with the processing shown in FIG.

  The image processor 4 determines whether there is an unprocessed frame image in the video image input to the image input unit 3 (s10). If there is an unprocessed frame image, the image processor 4 updates the frame image to be processed to the previous frame image in time (s11), and returns to s1.

  If there is no unprocessed frame image in the video image input to the image input unit 3, the image processing processor 4 performs attribute determination processing for a person whose attribute has not been determined at this time (s12). s12 is the same process as s9, and is provided to determine the attribute of the person who is captured in the last frame image of the video image input to the image input unit 3.

  Here, the attribute determination processing according to s9 and s12 will be described. FIG. 4 is a flowchart showing this attribute determination processing. The processing according to s9 and 12 corresponds to the attribute determination step in the present invention.

  The image processor 4 repeatedly performs the process shown in FIG. 4 for each subject whose attribute is to be determined. That is, FIG. 4 shows an attribute determination process for one target person.

  The image processor 4 reads the object map created for the subject (s21). In this object map, as described above, for each frame image in which the subject has been imaged, a detection record in which the captured image of the subject cut out from the frame image and the position (coordinates) on the frame image are associated with each other Is registered.

  The image processor 4 detects the movement path and movement speed of the subject from the object map read in s21 (s22). The movement path is obtained from the position (coordinates) on the frame image of each detection record registered in the object map. The moving speed is obtained from the amount of change in the position on the frame image. To that end, the relationship between the distance on the frame image and the distance on the real space is required. If the video image input to the image input unit 3 is a video image captured by a video camera installed at a specific location, the relationship between the distance on the frame image and the distance on the real space should be set in advance. Thus, the moving speed of the subject in real space can be detected.

  On the other hand, when the video image input to the image input unit 3 is not a video image captured by a specific video camera (when the video camera capturing the video image input according to the situation at that time is different), It is difficult to preset the relationship between the distance on the frame image and the distance on the real space. For this reason, in this example, the moving speed on the frame image is not detected, but the moving speed on the frame image is detected.

The image processor 4 determines whether the subject is moving in the direction in which the face is imaged from the movement path of the subject detected in s22 (s23). For example, when the moving direction of the subject is a direction away from the video camera that captured the video image, it is determined that the subject is moving in a direction in which the face is not captured. Further, when the moving direction of the subject is a direction approaching the video camera that captured the video image, it is determined that the subject is moving in the direction in which the face is captured.

  If the image processor 4 determines in s23 that the subject is moving in the direction in which the face is imaged, it determines whether or not the attribute other than the moving speed is applicable (s24). In this example, it is determined whether (1) the above-described mask is applied as an attribute relating to appearance, and (2) whether sunglasses are worn. Further, it is determined whether or not (4) the face is moved so as not to be imaged as an attribute relating to the state.

  If the image processor 4 determines in s23 that the subject has not moved in the direction in which the face is imaged, the image processor 4 does not perform the process related to s24.

  FIG. 5 is a flowchart showing a determination process for attributes other than the moving speed according to s24. The image processor 4 uses the detection record registered in the object map of the subject to acquire the subject's movement vector between temporally consecutive frame images (s31). The image processor 4 detects the horizontal component of the angle of the video camera that has captured the video image input to the image input unit 3 (s32), and the straight line and the angle formed by this horizontal component are the smallest. The frame image from which the vector is obtained (the frame image that is later in time) is determined (s33). In s33, a frame image is determined in which it is highly likely that the subject is facing the front of the video camera, that is, the subject's face is likely to be imaged.

  The image processor 4 performs a first face image detection process on the target person's image cut out from the frame image determined in s33 (an image registered in the detection record) (s34). This first face image detection process is a process based on an algorithm in which an image of a person who is not wearing a mask is input and learning of face extraction is performed on the image.

  If the face image can be detected by the first face image detection process in s34, the image processor 4 determines that the subject is not wearing a mask (s35, s36). On the other hand, if the face image cannot be detected in the first face image detection process in s34, the image processor 4 performs the second face image detection process on the target image cut out from the frame image determined in s33. (S37). This second face image detection process is a process based on an algorithm in which an image of a person wearing a mask is input and learning of face extraction is performed on the image.

  In this example, by performing the first face image detection process and the second face image detection process, it is possible to prevent the person wearing the mask from making an erroneous determination that the face is not captured. doing.

  If the face image can be detected by the second face image detection process in s37, the image processor 4 determines that the subject is wearing a mask (s38, s39). On the other hand, if the face image cannot be detected in the second face image detection process in s37, the image processor 4 determines whether there is a detection record (unprocessed detection record) that has not processed the clipped image. (S40). If there is an unprocessed detection record, the image processor 4 determines a frame image in which a straight line relating to the horizontal component of the angle of the video camera and a movement vector having the next smallest angle are obtained (s41). The process after s34 described above is performed on the frame image.

  If the image processor 4 determines that there is no unprocessed detection record in s40, the image processor 4 determines that the subject is moving so that the face is not captured (s42). This s42 is determination of the attribute concerning the state of the subject.

  In this example, the subject whose face is detected in the first face image detection process in s34 is determined not to have a mask without performing the second face image detection process. The first face image detection process and the second face image detection process may be executed, and the determination may be made based on the detection accuracy of the face image by each process.

  Further, the image processor 4 determines whether or not the person wearing the mask is wearing sunglasses for the person who is determined not to wear the mask in s36 and the person who is determined to be wearing the mask in s39 (s43). In s43, when there is a frame of glasses on the subject's face and the brightness of the periphery of the eye (the lens part inside the detected frame) is lower than a predetermined value compared to the brightness of a part such as the nose or cheek It is determined that you are wearing sunglasses.

When the process related to s24 is completed, the image processor 4 determines the attribute related to the moving speed of the subject (s25). As described above, this example is not a configuration for detecting the moving speed of the subject in the real space but a configuration for detecting the moving speed of the target on the frame image. The image processor 4 obtains the average moving speed Vave of the person on the frame image. This average moving speed Vave is an average value of the moving speed V detected for a plurality of persons captured in the video image input to the image input unit 3. In s25, by comparing the moving speed V of the subject person with the average moving speed Vave, it is determined whether or not the moving speed V of the subject person is faster than other people. Specifically, the image processor 4
Movement speed V> Average movement speed Vave + α (where α is a predetermined correction constant)
If it is, it will determine with a moving speed being a target person.

  The image processor 4 creates a record for the target person based on the attribute determination result determined in the above-described processing, and registers it in the attribute determination result DB 5 shown in FIG. 2 (s26).

Next, output image generation processing will be described. As described above, a person who is captured in the video image input to the image input unit 3
(1) Whether you have a mask,
(2) Whether wearing sunglasses (3) Whether moving speed is fast,
(4) Whether the face is moving so that it is not imaged,
These four attributes are registered in the attribute determination result DB 5 in association with the determination results determined as to whether they are applicable. FIG. 6 is a flowchart showing output image generation processing.

  The operator uses the operation unit 6 to perform an input operation related to designation of the type of attribute of the object. The image processor 4 accepts the attribute type of the object designated by the input operation performed by the operator on the operation unit 6 (s51). The number of attribute types accepted in s51 may be any number as long as it is one or more. The processing according to s51 corresponds to the attribute designation receiving step referred to in the present invention.

  The image processor 4 searches the attribute determination result DB 5 and extracts a target person who is determined to be applicable to the type of attribute received in s51 (s52). When there are a plurality of types of attributes received in s51, the image processor 4 may perform processing for extracting a target person who is determined to be applicable to all the received types of attributes, or any of the types of received types. It is good also as a structure which extracts the subject who determined with applying about an attribute.

  The image processor 4 generates, as an output image, a thumbnail image that displays a list of the face images of each subject extracted in s52 (s53). The processing according to s53 corresponds to the output image generation step referred to in the present invention. The image processor 4 outputs the thumbnail image generated in s52 from the output unit 7 (s54). The thumbnail image is displayed on a display device or the like connected to the output unit 7. The processing according to s54 corresponds to an output step in the present invention.

  FIG. 7 is a diagram showing an example of the thumbnail image display screen. FIG. 7 shows an example when the type of the designated attribute is “with mask”.

  Therefore, if you know the appearance characteristics (such as wearing a mask or wearing sunglasses), the time and effort required to confirm the person in the video image can be saved. It is done. In addition, it is possible to narrow down the objects to be checked with an attribute relating to a state where the moving speed is fast.

  In the above example, a thumbnail image that displays a list of human face images corresponding to the specified type of attribute is generated and output as an output image. However, a video image input to the image input unit 3 is captured. In addition to displaying a list of face images of all the people who have been assigned, for those who apply to the attributes of the specified type, images that are emphasized compared to other people, for example, the border of the face image is thickened or the color is changed. Different images may be generated as output images.

  Next, the reproduction process will be described. FIG. 8 is a flowchart showing this reproduction processing.

  The image processor 4 receives the designation of the displayed face image in the output image shown in FIG. 7 (s61). The image processor 4 determines the ID of the person whose face image is designated (s62). The image processor 4 searches the attribute determination result DB 5 using the ID determined in s62 as a key, and acquires the reproduction start position of the corresponding person (s63). The image processor 4 starts playback of the video image input to the image input unit 3 from the playback position acquired in s63 (s64). This s64 is a configuration corresponding to the reproducing unit referred to in the present invention. That is, the image processor 4 also has a configuration corresponding to the playback unit referred to in the present invention.

  Note that a video image to be reproduced is recorded (recorded) on a medium (not shown) such as a hard disk connected to the image input unit 3. The medium may be built in the image processing apparatus 1 or may be externally attached to the image processing apparatus 1.

  Thereby, a person in charge such as a guard can easily confirm a video image in which a person related to the face image is captured by designating the face image.

In the above example,
(1) Whether you have a mask,
(2) Whether wearing sunglasses (3) Whether moving speed is fast,
(4) Whether the face is moving so that it is not imaged,
However, the type of attribute to be determined is not limited to this.

Further, in the above example, the type of the target object is human, but other moving bodies may be used. For example, when the target object type is a vehicle,
(A) whether the license plate is hidden,
(B) Whether the license plate number written on the license plate is hidden (the license plate itself is not hidden),
(C) It is determined whether or not the driver's face is hidden from the front side of the vehicle as an attribute related to appearance,
(D) Whether the moving speed is fast,
(E) whether you are running backwards,
(F) whether it is meandering,
(G) What is necessary is just to determine whether the no-light is running, etc. as an attribute concerning a state.

  (A) should just determine with the number plate being hidden, when the number plate of the vehicle is not found by processes, such as pattern matching with respect to the frame image in which the vehicle is imaged. In addition, (b) is a character recognition process for a written character (number plate number), although a license plate of the vehicle was found by processing such as pattern matching for a frame image in which the vehicle is imaged. When the license plate number cannot be recognized, it may be determined that the license plate number is hidden. (C) is a frame image obtained by imaging the vehicle from substantially the front, when the driver's face cannot be detected by both the first face image detection process and the second face image detection process described above. It may be determined that the driver's face is hidden from view.

  Moreover, what is necessary is just to determine similarly to the case of the person mentioned above (d). Further, (e) and (f) may be determined from the moving route of the vehicle. Furthermore, (f) should just determine with the vehicle which is driving | running with no light in the situation where most vehicles are lighting the headlamp, and the vehicle which is not lighting the headlamp. Whether or not the headlamp is lit can be determined based on whether or not there is a region with high luminance on both the left and right sides of the vehicle in the captured frame image.

  In this case as well, if the vehicle is characterized by appearance, the time and labor required for confirming the corresponding vehicle captured in the video image can be reduced. In addition, it is possible to narrow down the objects to be checked with an attribute relating to a state where the moving speed is fast.

  Further, the type of the target object is not limited to the above-described person or vehicle, but may be other types of moving objects. Further, the type of object to be targeted is not limited to one type, and may be a plurality of types. In this case, it is preferable to create the attribute determination result DB 5 shown in FIG. 2 separately for each target object type.

DESCRIPTION OF SYMBOLS 1 ... Image processing apparatus 2 ... Control part 3 ... Image input part 4 ... Image processor 5 ... Attribute determination result database (attribute determination result DB)
6 ... Operation part 7 ... Output part

Claims (6)

An image input unit for inputting a video image;
Whether the frame image applied to the video image input to the image input unit is processed, and for the object being imaged, whether the attribute relating to the appearance of the predetermined object and the attribute relating to the state of the object apply to the attribute An attribute determination unit for determining
An attribute designation accepting unit for accepting specification of an object attribute;
An output image generating unit that generates an output image that distinguishes an object determined by the attribute determining unit from other objects for the attribute of the object received by the attribute designation receiving unit;
An output unit that outputs the output image generated by the output image generation unit,
The attribute determination unit determines, as an attribute related to the state of the object, at least whether the moving speed of the object is faster than other objects based on the average moving speed of the object on the frame image, not in real space. An image processing apparatus that makes a determination. The output image generating unit, the attributes of the object received by the attribute designation receiver, the object is determined that the attribute determining unit applies, to generate a thumbnail image to be displayed in a list as the output image, in claim 1 The image processing apparatus described. For each object captured in the video image input to the image input unit, a determination is made as to whether the image of the object and a plurality of types of attributes predetermined by the attribute determination unit apply to the attribute. The image processing apparatus according to claim 1 , further comprising an attribute determination result storage unit that stores the results in association with each other. When any object included in the output image output by the output unit is selected and specified, a playback unit that plays back the position where the object is captured in the video image input to the image input unit is provided. the image processing apparatus according to any one of claims 1-3. Whether a frame image applied to a video image input to the image input unit is processed, and for an object being imaged, an attribute relating to the appearance of a predetermined object and an attribute relating to the state of the object, whether the attribute applies An attribute determination step for determining;
In the attribute designation accepting unit, an attribute designation accepting step for accepting designation of the attribute of the object;
An output image generating step for generating an output image that distinguishes an object that has been determined to be applicable to the attribute determination step with respect to the attribute of the object received in the attribute designation reception step;
An output processing for outputting an output image generated in the output image generation step from an output unit, and an image processing method that a computer executes,
In the attribute determination step, as an attribute related to the state of the object, at least whether or not the moving speed of the object is faster than other objects is based on the average moving speed of the object on the frame image, not in the real space. An image processing method that is a step of determining by Whether a frame image applied to a video image input to the image input unit is processed, and for an object being imaged, an attribute relating to the appearance of a predetermined object and an attribute relating to the state of the object, whether the attribute applies An attribute determination step for determining;
In the attribute designation accepting unit, an attribute designation accepting step for accepting designation of the attribute of the object;
An output image generating step for generating an output image that distinguishes an object that has been determined to be applicable to the attribute determination step with respect to the attribute of the object received in the attribute designation reception step;
An output processing for outputting an output image generated in the output image generation step from an output unit, and an image processing program for causing a computer to execute the output step,
In the attribute determination step, as an attribute related to the state of the object, at least whether or not the moving speed of the object is faster than other objects is based on the average moving speed of the object on the frame image, not in the real space. An image processing program that is a step of determining by

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