WO2022224639A1 - Dispositif de reconnaissance d'objet et procédé de commande de dispositif de reconnaissance d'objet - Google Patents

Dispositif de reconnaissance d'objet et procédé de commande de dispositif de reconnaissance d'objet Download PDF

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WO2022224639A1
WO2022224639A1 PCT/JP2022/011803 JP2022011803W WO2022224639A1 WO 2022224639 A1 WO2022224639 A1 WO 2022224639A1 JP 2022011803 W JP2022011803 W JP 2022011803W WO 2022224639 A1 WO2022224639 A1 WO 2022224639A1
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partial
image
registered
images
priority
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PCT/JP2022/011803
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Japanese (ja)
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翔哉 村上
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オムロン株式会社
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions

Definitions

  • the present invention relates to an object recognition device.
  • a face recognition system that recognize the user's face and identify whether the user has the authority to perform a specific action.
  • a face recognition system is used as a device for permitting entrance/exit to an area with high security or as a device for issuing permission to use a specific device.
  • Patent Literature 1 discloses a technique that enables normal face recognition even when the user wears a mask or changes his or her hairstyle. By emphasizing the feature amount of a certain part and reducing the feature amount of other parts, even if there is a difference from the data registered in the database, the face can be recognized normally.
  • Patent Document 2 is an invention that recognizes a face when a captured image of the user's face differs from the image registered in the database due to a mask, sunglasses, hat, or the like. According to the above example, when there is a difference between the captured image and the registered image in the database, instead of immediately failing face recognition, the captured image is divided into multiple areas, and the area where matching fails is displayed to the user. It is a technology that makes face recognition successful by notifying and prompting re-recognition.
  • Japanese Patent Application Laid-Open No. 2002-200000 describes an invention relating to a digital camera, and is a technology that enables priority recognition of a subject by defining the priority of the subject for each shooting mode, and performs optical adjustment according to the subject at an early stage. be.
  • Japanese Patent Laid-Open No. 2004-100002 recognizes a similar pattern for each region divided into a plurality of regions for a pattern image of a living body such as a vein pattern, and saves a number corresponding to the pattern for each region, thereby obtaining a pattern image of the living body. It is an invention that reduces the capacity of
  • Patent Document 5 face recognition is performed using a low-resolution image, and if the image is determined to be the same image, face recognition is performed using a portion of a higher-resolution image, thereby gradually increasing the speed while ensuring speed. It is an invention that improves the accuracy of face recognition.
  • Japanese Patent Application Laid-Open No. 2007-257221 Japanese Patent Application Laid-Open No. 2019-168929 Japanese Patent Application Laid-Open No. 2007-068149 Japanese Patent Application Laid-Open No. 2011-065315 Japanese Patent Application Laid-Open No. 2012-238059
  • an object of one aspect of the present invention is to realize a device that can perform object recognition at high speed while maintaining recognition accuracy.
  • an object recognition apparatus includes an image acquisition unit that acquires a captured image of a target object; an image extracting unit that creates a plurality of partially captured images obtained by extracting the images of the above, a plurality of registered partial images that are obtained by extracting images of a plurality of predetermined portions of a registered object as a recognition target stored in a storage unit; a matching unit that performs matching with the partially captured images in order according to the priority levels associated with the respective registered partial images; a recognition output unit that outputs a recognition result.
  • An object recognition apparatus includes an image acquisition step of acquiring a captured image of a target object; an image extracting step for creating; a plurality of partial registration images obtained by extracting images of a plurality of predetermined portions of a registered object as a recognition target stored in a storage unit; and a recognition output step of outputting the recognition result of the target object when the matching in the matching unit satisfies a predetermined condition.
  • a partially captured image extracted from a captured image and a previously registered partially registered image are collated with a priority associated with the partially registered image, and the collation result is a predetermined value. Recognition can be terminated early when the conditions of
  • FIG. 2 is a block diagram showing the configuration of the main parts of the face recognition system according to Embodiment 1;
  • FIG. 3A and 3B are model diagrams showing a captured image and a partially captured image according to the first embodiment;
  • FIG. 10 is a flow chart showing a flow of registering a partial registration image;
  • 5 is a flow chart showing the flow of operation of operation example 1 according to the first embodiment.
  • 9 is a flow chart showing the flow of operation of operation example 2 according to the first embodiment;
  • 9 is a flow chart showing the flow of operation of operation example 3 according to the first embodiment;
  • 10 is a flow chart showing the flow of operation of operation example 4 according to the first embodiment;
  • FIG. 11 is a block diagram showing the configuration of the main part of the face recognition system according to Embodiment 2;
  • 13A and 13B are model diagrams showing a captured image and a partially captured image according to Embodiment 3;
  • FIG. 1 is a block diagram showing the configuration of a main part of a face recognition system 100 according to the first embodiment.
  • the face recognition system 100 includes a camera 20 that captures a captured image including a face, a face recognition device (object recognition device) 10 that performs face recognition on the captured image, and an electromagnetic lock 30 that is controlled by the face recognition device 10. .
  • the face recognition device 10 extracts a partial captured image corresponding to a pre-registered partial registration image from the captured image, and performs matching by comparing the partial captured image and the partial registered image.
  • a plurality of partial registration images are prepared, and a priority is set for each partial registration image. Collation with respect to each partial registration image is performed in the order according to the priority.
  • the face recognition device 10 can be broadly divided into two modes: a mode that prioritizes personal recognition speed for recognizing that the target person for face recognition is a registrant, and a mode that recognizes that the target person for face recognition is not a registrant. This is a mode that gives priority to other person recognition speed. In the mode that prioritizes personal recognition speed, when a pair of a set of partially captured image and partially registered image is recognized as the same image, it is recognized as substantially the same face. On the other hand, in the mode that prioritizes other person recognition speed, when a pair of a set of partially captured images and partially registered images can be recognized as different images, it is recognized that they are not substantially the same face. When recognizing substantially the same face, the face recognition device 10 releases the electromagnetic lock 30 .
  • the face recognition device 10 performs matching in the order according to the priority, and can output the result of face recognition when the recognition result of one set of the partially captured image and the partially registered image is obtained. Therefore, the recognition result can be output earlier than when face recognition is performed on the entire captured image.
  • the configuration of the face recognition system 100 will be described based on FIG.
  • the face recognition device 10 includes an image acquisition section 11 , a storage section 12 , an image extraction section 13 , a matching section 14 and a recognition output section 15 .
  • the camera 20 is a camera that captures a captured image including the face of the target for face recognition.
  • the camera 20 outputs the captured image to the image acquisition section 11 .
  • the electromagnetic lock 30 is an electronic lock controlled by the face recognition device 10.
  • the electromagnetic lock 30 is not limited to an electronic lock, but may be any program-controlled device or program, and the function of the device or program cannot be used unless it is unlocked.
  • the door cannot be opened to enter the interior unless the electromagnetic lock 30 is unlocked by face recognition.
  • the smart phone does not accept an operation unless the electromagnetic lock 30 is unlocked (released) by face recognition.
  • the image acquisition unit 11 inputs the captured image.
  • the image acquisition unit 11 outputs the input captured image to the image extraction unit 13 .
  • the storage unit 12 stores a plurality of partial registration images for each registrant who is a target of face recognition. In addition to each partial registration image, the storage unit 12 also stores the priority, and the order of performing face recognition on the partial registration images is determined.
  • the partial registration image and priority information are stored in a storage unit outside the face recognition device 10, and even if the face recognition device 10 reads out the partial registration image and priority information through various communication means, good.
  • the image extracting unit 13 extracts a portion corresponding to the partial registered image from the input captured image and sets it as a partial captured image.
  • the image extraction unit 13 outputs the plurality of extracted partial captured images to the matching unit 14 .
  • the matching unit 14 compares the input partial captured image and the partial registered image, and calculates a numerical value called similarity indicating how similar they are to each other. After that, the matching unit 14 compares the degree of similarity with a predetermined threshold to determine whether the images are substantially the same. Also, the partially registered image of a certain priority and the partially captured image corresponding to the partially registered image are collated, and if necessary, the partially registered image of the next priority and the partially captured image corresponding to the partially registered image are matched. Perform matching processing. Collation necessary for face recognition is performed, and when the collation result is determined, the collation unit 14 outputs the collation result to the recognition output unit 15 .
  • the recognition output unit 15 receives the collation result input and determines whether or not to issue a signal to unlock the electromagnetic lock 30 .
  • the recognition output unit 15 unlocks the electromagnetic lock 30 when the matching result indicates that the target person for face recognition is the registrant.
  • the recognition output unit 15 does not unlock the electromagnetic lock 30 when the matching result indicates that the target person for face recognition is not the registrant.
  • FIG. 2 is a model diagram showing a captured image 111 and a partially captured image 112 according to the first embodiment.
  • the captured image 111 is, as shown in FIG. 2, an image that captures the entire face of the target person to be subjected to face recognition.
  • the partial captured images 112 are, for example, partial images of the five captured images 111, and are partial captured images 112a to 112e. Each partial captured image is an image obtained by partially capturing a part representing features of the face.
  • the partially captured image 112a is an image of both eyes
  • the partially captured image 112b is a mouth
  • the partially captured image 112c is a hair
  • the partially captured image 112d is a nose
  • the partially captured image 112e is an image of a forehead.
  • the ranges of the partial captured images 112 may overlap each other.
  • both the partially captured image 112a and the partially captured image 112e include eyebrows.
  • the partial captured image 112 is extracted from the captured image 111 by the image extraction unit 13, and the extracted range is the range corresponding to the partial registered image.
  • the image extracting unit 13 extracts from the captured image 111 the partial captured images 112 respectively corresponding to the registered partial images. At this time, in order to extract the partial captured image 112 , pattern matching may be performed on the captured image 111 to derive the range of the partial captured image 112 .
  • the method of extracting the partial captured image 112 is not limited to this method, and the position of the partial area to be extracted from the captured image 111 may be determined in advance, and the corresponding partial area may be extracted as the partial captured image 112 .
  • FIG. 3 is a flow chart showing the flow of registering a partial registration image.
  • it is necessary to preliminarily register partial registration images obtained by dividing a face image into parts.
  • the camera 20 captures the face image of the registrant to be registered.
  • the captured face image is extracted for each part of the face.
  • the parts of the face include the eyes, mouth, nose, eyebrows, forehead, hair, etc., and may be extracted as an image that captures the periphery in addition to each part. This operation is performed by the user operating the face recognition device 10, or automatically performed by the face recognition device 10 according to a predetermined rule.
  • each divided part is registered in the storage unit 12 as a partial registered image.
  • a priority which is the order in which face recognition is performed, is assigned to each partial registration image.
  • priority assignment may be performed manually by the user, or may be performed automatically by the face recognition device 10 according to a predetermined rule.
  • FIG. 4 is a flowchart showing the operation flow of operation example 1 according to the first embodiment.
  • Operation example 1 is an operation in which, when a partially registered image to be subjected to face recognition is a face image of one person, priority is given to speed of person recognition for a registrant of the partially registered image. To simplify the explanation, it is assumed that there are five partial registration images.
  • the camera 20 captures a face image
  • the image acquisition unit 11 acquires the face image as a captured image.
  • i is a natural number indicating the priority of the partially registered image.
  • the image extraction unit 13 extracts the partial captured image corresponding to the partial registered image with i-th priority.
  • the collation unit 14 compares the partial captured image and the partial registered image with the i-th priority for collation. If the partial captured image and the partial registered image substantially match, the process proceeds to S25. If the partial captured image and the partial registered image do not substantially match, the process proceeds to S26.
  • the matching unit 14 recognizes that the target person is the same person as the single registrant because the partial captured image and the partial registered image substantially match, and exits the matching loop. After that, the recognition output unit 15 unlocks the electromagnetic lock 30 .
  • the recognition output unit 15 recognizes that the target person is different from the registrant because the target person is not the same person as the registrant. Therefore, the recognition output unit 15 does not unlock the electromagnetic lock 30 .
  • the processing when it is determined that one partial captured image substantially matches the partial registered image, it is possible to quickly recognize that the target person is the same person as the registered person. Also, in order to ensure security, it is preferable to set a rather strict similarity threshold for judging that the partially captured image and the partially registered image substantially match each other. By setting the threshold to be rather strict, it is possible to suppress the possibility that a target person other than the registrant is recognized as the same person by face recognition.
  • conditional branching is performed depending on whether or not one partial captured image substantially matches the partial registered image, and if the condition is met (Yes in S24), the electromagnetic lock 30 is released (S25 ) does not necessarily have to be canceled based on the result of recognition based on one partially captured image. That is, when a predetermined number of partially captured images substantially match the partially registered images, it may be recognized that the subject is the same person as the single registrant. Security is improved by increasing the number of partially registered images required to determine that the person is the same person.
  • it is preferable that the number of partial registration images necessary for determining that the person is the same person is smaller than the number of partial registration images stored in the storage unit 12 . This makes it possible to output matching results at a higher speed than when matching with all partially registered images.
  • example 1 it is preferably used for face recognition with a device that is basically used only by registrants.
  • a device that is basically used only by registrants.
  • face recognition is used as user recognition.
  • FIG. 5 is a flowchart showing the operation flow of Operation Example 2 according to the first embodiment.
  • Operation example 2 is an operation that gives priority to the other person recognition speed for recognizing that the person is not the registrant of the partial registration image when the partial registration image to be subjected to face recognition is the face image of one person. To simplify the explanation, it is assumed that there are five partial registration images.
  • the collation unit 14 compares the partial captured image and the partial registered image with the i-th priority for collation. If the partial captured image and the partial registered image substantially match, the process proceeds to S36. If the partial captured image and the partial registered image do not substantially match, the process proceeds to S35.
  • the matching unit 14 recognizes that the target person is different from the single registrant because the partial captured image and the partial registered image do not substantially match, and exits the matching loop. After that, the recognition output unit 15 does not unlock the electromagnetic lock 30 .
  • the recognition output unit 15 recognizes that the target person is the same person as the registrant because the partial captured images corresponding to all the partial registration images substantially match. Therefore, the recognition output unit 15 unlocks the electromagnetic lock 30 .
  • the similarity threshold for judging that the partially captured image and the partially registered image match each other is set loosely. It is preferable to keep Due to the loose threshold setting, even a subject who is not a registrant may be judged to match substantially in matching per part, but by using a large number of parts in a matching loop, as a result, registration A target person who is not a person can be output as a person different from the registrant.
  • conditional branching is performed depending on whether or not one partial captured image substantially matches the partial registered image, and if the condition is not satisfied (No in S34), the recognition process is terminated.
  • the process does not necessarily end with a recognition result based on one partially captured image. That is, if a predetermined number of partially captured images do not match the partially registered images, it may be recognized that the target person is not the same person as the registered person. Misjudgment can be suppressed by increasing the number of necessary partial registration images.
  • it is preferable that the number of partially registered images required to determine that the person is not the same person is smaller than the number of partially registered images stored in the storage unit 12 . This makes it possible to output matching results at a higher speed than when matching with all partially registered images.
  • example 2 it is preferably used to prevent misuse by others of a device that is basically used only by a registrant. For example, when an electronic device such as a smartphone owned by an individual is lost, it is used to improve security for unlocking by face authentication.
  • FIG. 6 is a flow chart showing the operation flow of operation example 3 according to the first embodiment.
  • Operation example 3 is an operation that prioritizes the person recognition speed for the person in the partial registration image when facial images of a plurality of persons are registered in the partial registration image to be subjected to face recognition. In order to simplify the explanation, it is assumed that there are three registrants and that each registrant has five partially registered images.
  • the camera 20 captures a face image
  • the image acquisition unit 11 acquires the face image as a captured image.
  • i is a natural number indicating the priority of the partially registered image.
  • j is a natural number representing a registrant.
  • the image extraction unit 13 extracts the partial captured image corresponding to the partial registered image with the i-th priority for the j-th registrant.
  • the collation unit 14 compares the partially captured image with the partially registered image of the i-th priority for the j-th registrant to perform collation. If the partial captured image and the partial registered image substantially match, the process proceeds to S46. If the partial captured image and the partial registered image do not substantially match, the process proceeds to S47.
  • the matching unit 14 recognizes that the target person is the same person as one of the registrants because the partial captured image and the partial registered image substantially match, and exits the matching loop. After that, the recognition output unit 15 unlocks the electromagnetic lock 30 .
  • the recognition output unit 15 recognizes that the target person is different from the multiple registrants because the target person does not substantially match all of the multiple registrants. Therefore, the recognition output unit 15 does not unlock the electromagnetic lock 30 .
  • the target person when it is determined that one partially captured image substantially matches the partially registered image of any one of a plurality of registrants, the target person is the registrant. It recognizes that it is the same person as one of them, and terminates the face recognition. Therefore, the target person's face can be recognized early. Also, in order to ensure security, it is preferable to set a rather strict similarity threshold for judging that the partially captured image and the partially registered image substantially match each other. By setting the threshold to be rather strict, it is possible to suppress the possibility that a target person who is not a plurality of registrants will be recognized as the same person as one of the plurality of registrants by face recognition.
  • it is a device that is less likely to be matched by a target person other than a registrant, and is preferably used when face recognition is performed by a device used by multiple registrants.
  • it can be used for the purpose of allowing registrants to enter an entrance gate that is basically expected to be entered by related parties.
  • FIG. 7 is a flowchart illustrating the operation flow of Operation Example 4 according to the first embodiment.
  • Operation example 4 is an operation that prioritizes the recognition speed of others other than the person in the partial registration image when facial images of a plurality of persons are registered in the partial registration image to be subjected to face recognition. In order to simplify the explanation, it is assumed that there are three registrants and that each registrant has five partially registered images.
  • the collation unit 14 compares the partially captured image with the partially registered image of the i-th priority for the j-th registrant to perform collation. If the partial captured image and the partial registered image do not substantially match, the process proceeds to S56. If the partial captured image and the partial registered image substantially match, the process proceeds to S57.
  • the matching unit 14 determines that the target person is not the j-th registrant. Therefore, in subsequent processing, the j-th registrant is excluded from candidates, and subsequent verification is not performed.
  • the collation unit 14 determines whether there are any candidate registrants remaining among the plurality of registrants. If there are no candidate registrants left, the process proceeds to S59. If candidate registrants remain, the process proceeds to S60.
  • the matching unit 14 recognizes that the target person is a different person from any one of the plurality of registrants because there is no partially registered image that substantially matches the partially captured image, and performs a matching loop. go through. After that, the recognition output unit 15 does not unlock the electromagnetic lock 30 .
  • the recognition output unit 15 recognizes that the target person is the same person as one of a plurality of registrants because there is a registrant whose partial captured images corresponding to all of the partial registration images substantially match. do. Therefore, the recognition output unit 15 unlocks the electromagnetic lock 30 .
  • the subject when it is determined that one partially captured image does not substantially match the partially registered image of any one of the plurality of registrants, the subject becomes the registrant. Since the target person can be recognized as different from the target person, the target person can be recognized as a stranger at an early stage. However, in order not to erroneously recognize a registrant as someone else, it is preferable to loosely set a similarity threshold for judging that the partial captured image and the partially registered image substantially match each other.
  • the threshold setting is loose, even a subject who is not a registrant may be judged to match substantially in matching per part, but by using a large number of parts in a matching loop, as a result, the registrant It is possible to output a non-existent target person as a person different from the registrant.
  • the partially captured image and the partially registered image are collated, and when the collation does not substantially match, the registrant is excluded from multiple registrant candidates. Therefore, by proceeding with collation, the number of candidates for multiple registrants is narrowed down. As a result, when the target person is the same person as any one of a plurality of registrants, even when the electromagnetic lock is unlocked, it can be unlocked faster than when collating by round-robin.
  • it is a device that is highly likely to be matched by a target person other than a registrant, and is preferably used when face recognition is performed by a device used by multiple registrants. For example, at an entrance gate where an unspecified number of people are expected to enter, it is conceivable that only registrants are permitted to enter. It is used as a high-security electromagnetic lock for entry/exit gates because it is determined that the person is the same person when all parts are substantially matched.
  • the matching unit can determine whether or not the partial registered image and the partial captured image corresponding to the partial registered image substantially match from the calculated degree of similarity.
  • the target person is identified as the registrant when a combination in which at least one partial registered image and a partially captured image substantially match is obtained. recognize as a person.
  • priority is given to the recognition speed of others, it is recognized that the target person is not the same person as the registrant when a combination in which at least one partially registered image and the partially captured image substantially match is obtained. do.
  • the target person is identified as the registered person at the time when a combination of the partially registered image and the partially captured image of at least one part that do not substantially match is obtained. It is determined that the person is not a person, and in subsequent processing, face recognition is performed after removing the registrant from candidates.
  • the result of face recognition can be influenced by image recognition of a certain part. Therefore, face recognition can be terminated early.
  • FIG. 8 is a block diagram showing the configuration of the essential parts of the face recognition system 100a according to the second embodiment.
  • the face recognition system 100a is different from the face recognition system 100 in that the face recognition device 10a is provided with a priority setting unit 16.
  • FIG. 8 is a block diagram showing the configuration of the essential parts of the face recognition system 100a according to the second embodiment.
  • the face recognition system 100a is different from the face recognition system 100 in that the face recognition device 10a is provided with a priority setting unit 16.
  • the priority setting unit 16 is a functional block that optimizes the priority of each partial registration image based on the similarity history of past face recognition results.
  • the priority setting unit 16 first learns the similarity tendency based on the similarity history for each partially registered image. As an example, the priority setting unit 16 calculates the average similarity based on the similarity history.
  • the priority setting unit 16 assigns priority to each partial registration image in descending order of average similarity.
  • partially registered images with high priority tend to have a high degree of similarity, and face recognition can be completed early.
  • priority setting unit 16 assigns priorities in descending order of average similarity. As a result, a partially registered image with a high priority tends to have a low degree of similarity to others, and face recognition can be completed early.
  • the priority optimization process may be performed at any time while the face recognition device 10a is not performing the face recognition process, so that the face recognition can always be performed with the optimum priority.
  • the priority optimization in the priority setting unit 16 may not be performed automatically, and may be manually set in any order of priority by user operation.
  • the priority setting unit 16 causes the display device provided in the face recognition device 10a to display a list of partial registration images and the images, and the input device provided in the face recognition device 10a allows the user to set the priority of each partial registration image. Setting inputs may be accepted. Alternatively, priority setting information received from a user in an external terminal device may be obtained and set by the priority setting unit 16 via communication means.
  • the priority of the eyes is set to be higher and the mask is often masked, so the priority of the mouth is set lower.
  • priorities it is possible to set priorities according to one's own characteristics and preferences. For example, it is possible to set a low priority for the eyes because the user often wears sunglasses, or set a low priority for the hair because the user often changes hairstyles. It becomes possible.
  • FIG. 9 is a model diagram showing a captured image 113 and a partially captured image 114 according to the third embodiment.
  • the captured image 113 is an image of an arbitrary object, and may be an image of an automobile as shown in FIG. 9, for example.
  • the partial captured images 114 are, for example, partial captured images 114a to 114d of the four captured images 113, respectively. Each partial captured image represents a feature of the object.
  • the partially captured image 114a is the side glass
  • the partially captured image 114b is the windshield
  • the partially captured image 114c is the headlight
  • the partially captured image 114d is the tire.
  • the ranges of the partial captured images 114 may overlap each other.
  • the method of creating the partial captured image 114 and the method of assigning priority to the partial captured image 114 are the same as those in the flow chart of the face recognition operation shown in FIG.
  • the flowchart of the operation in object recognition according to the third embodiment is the same as the flowchart of the operation in face recognition shown in FIGS.
  • the target object is imaged to obtain a captured image
  • a partial captured image corresponding to the partially registered image of the registered object is extracted from the captured image
  • the partially registered image and the partially captured image are compared.
  • an object recognition apparatus includes an image acquisition unit that acquires a captured image of a target object; an image extracting unit that creates a plurality of partially captured images obtained by extracting the images of the above, a plurality of registered partial images that are obtained by extracting images of a plurality of predetermined portions of a registered object as a recognition target stored in a storage unit; a matching unit that performs matching with the partially captured images in order according to the priority levels associated with the respective registered partial images; a recognition output unit that outputs a recognition result.
  • matching is repeated until a predetermined condition is met between the partially captured image and the partially registered image in the order of the priority associated with the partially registered image, so that the target object becomes the registered object. It can be determined whether or not Since the recognition result is output when the predetermined condition is satisfied, the recognition result of the target object can be output at an early stage.
  • the collation unit may perform collation by calculating a degree of similarity between the partial registered image and the partial captured image and comparing it with a predetermined threshold.
  • the recognition output unit may output the recognition result of the target object.
  • the matching unit determines that there is a partially captured image that substantially matches a partially registered image, it is possible to output a recognition result that the target object is a registered object. .
  • the storage unit stores the partial registration images and the priorities of the partial registration images with respect to a plurality of the registered objects, and the matching unit performs the partial registration of all the registered objects at a certain priority. After performing matching on the images, matching may be performed on the partially registered images of all the registered objects in the next priority.
  • the collation unit performs collation in the order according to the priority, and when it is determined that the partial registered image and the partial captured image corresponding to the partial registered image do not substantially match, the recognition output.
  • a unit may output a recognition result of the target object.
  • the matching unit determines that there is a partial captured image that does not substantially match the partial registered image, it is possible to output a recognition result that the target object is not a registered object. .
  • the storage unit stores the partial registration images and the priorities of the partial registration images with respect to a plurality of the target objects, and the matching unit performs the partial registration of all the registration objects at a certain priority. After matching the images, matching is performed with respect to the partial registered images of all the registered objects at the next priority, and the partial registered images and the partial captured images corresponding to the partial registered images are substantially If it is determined that they do not match, it is not necessary to collate the corresponding registered object at the next priority.
  • the matching unit may further include a priority setting unit that performs a process of storing the similarity calculation result as a similarity history, and sets a priority of the partially registered image based on the similarity history. .
  • a priority setting unit may be further provided for setting the priority of the partial registration image based on the user's input.
  • the priority of partially registered images can be arbitrarily set based on user input. Therefore, it is possible to change the priority of the part whose priority is to be intentionally lowered or the priority of the part to be intentionally raised.
  • the target object may be a person's face.
  • the object may be a person's face, which can be used for early face recognition.
  • An object recognition apparatus includes an image acquisition step of acquiring a captured image of a target object; an image extracting step for creating; a plurality of partial registration images obtained by extracting images of a plurality of predetermined portions of a registered object as a recognition target stored in a storage unit; and a recognition output step of outputting the recognition result of the target object when the matching in the matching unit satisfies a predetermined condition.
  • the object recognition device may be implemented by a computer.
  • the object recognition device is implemented by the computer by operating the computer as each part (software element) provided in the object recognition device.
  • An object recognition program for an object recognition device realized by a computer, and a computer-readable recording medium recording it are also included in the scope of the present invention.
  • the functions of the face recognition devices 10 and 10a and the object recognition device are programs for causing a computer to function as the devices. 10a) can be implemented by a program for causing a computer to function.
  • the device comprises a computer having at least one control device (eg processor) and at least one storage device (eg memory) as hardware for executing the program.
  • control device eg processor
  • storage device eg memory
  • the above program may be recorded on one or more computer-readable recording media, not temporary.
  • the recording medium may or may not be included in the device.
  • the program may be supplied to the device via any transmission medium, wired or wireless.
  • control blocks can be realized by logic circuits.
  • integrated circuits in which logic circuits functioning as the control blocks described above are formed are also included in the scope of the present invention.
  • control blocks described above it is also possible to implement the functions of the control blocks described above by, for example, a quantum computer.
  • each process described in each of the above embodiments may be executed by AI (Artificial Intelligence).
  • AI Artificial Intelligence
  • the AI may operate on the control device, or may operate on another device (for example, an edge computer or a cloud server).

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Human Computer Interaction (AREA)
  • Multimedia (AREA)
  • Collating Specific Patterns (AREA)
  • Image Analysis (AREA)

Abstract

Étant donné que la reconnaissance faciale prend beaucoup de temps, un utilisateur ne peut pas être mis au travail à un stade précoce. L'invention concerne un dispositif de reconnaissance faciale (10) comprenant : une unité de collation (14) qui collationne séquentiellement une pluralité d'images partiellement capturées obtenues par extraction des images de parties prédéterminées d'un sujet parmi des images capturées du sujet avec une pluralité d'images partiellement enregistrées qui sont des images de parties prédéterminées d'une cible de reconnaissance stockée dans une unité de stockage (12), selon des priorités respectivement associées aux images partiellement enregistrées; et une unité de sortie de reconnaissance (15) qui délivre un résultat de reconnaissance pour le sujet au moment où le résultat de collation de l'unité de collation satisfait une condition prédéterminée.
PCT/JP2022/011803 2021-04-23 2022-03-16 Dispositif de reconnaissance d'objet et procédé de commande de dispositif de reconnaissance d'objet WO2022224639A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008257327A (ja) * 2007-04-02 2008-10-23 Omron Corp 照合装置
JP2010146581A (ja) * 2010-01-13 2010-07-01 Fujifilm Corp 人物画像検索装置
JP2018049655A (ja) * 2015-09-08 2018-03-29 日本電気株式会社 顔認識装置、顔認識方法、顔認識プログラム、表示制御装置、表示制御方法および表示制御プログラム

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008257327A (ja) * 2007-04-02 2008-10-23 Omron Corp 照合装置
JP2010146581A (ja) * 2010-01-13 2010-07-01 Fujifilm Corp 人物画像検索装置
JP2018049655A (ja) * 2015-09-08 2018-03-29 日本電気株式会社 顔認識装置、顔認識方法、顔認識プログラム、表示制御装置、表示制御方法および表示制御プログラム

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