JP2023086948A - Information processing device - Google Patents

Abstract

To solve a problem such that it is difficult to smoothly pass a gate.SOLUTION: An information processing device 200 comprises: image processing means 220 for extracting a feature quantity of an object in a photographed image obtained by photographing a region before passage of a gate to store collation information concerning collation of the object based on the feature quantity; distance estimation means 230 for estimating a distance from the gate to the object in the photographed image; and collation means 240 for performing collation determination based on the estimated distance and collation information in which the object that estimated the distance is stored.SELECTED DRAWING: Figure 9

Description

The present invention relates to an information processing device, an information processing system, a program, and an information processing method.

2. Description of the Related Art As means for restricting or managing persons entering and exiting a specific place such as an office or an event site, a verification system is used to verify whether or not a person trying to pass through is a pre-registered person. In particular, in recent years, with the development of human face recognition technology, a walk-through face recognition system that performs face recognition from a person's face image captured by a camera installed at a gate has been used.

JP 2016-083225 A

Here, in the walk-through face authentication system, it is necessary to check the people lined up at the gate in order to open and close the gate so that the people can pass through the gate smoothly. However, there are various people trying to pass through the gate, and it is difficult to properly determine the order. As a result, there arises a problem that smooth passage through the gate is difficult.

SUMMARY OF THE INVENTION Accordingly, an object of the present invention is to solve the above-described problem of difficulty in smoothly passing through a gate.

An information processing device according to one aspect of the present invention includes:
image processing means for extracting a feature amount of an object in a photographed image of an area before passage through a gate and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
with
take the configuration.

Further, an information processing system, which is one embodiment of the present invention,
an imaging means for acquiring a photographed image of the area before passing through the gate;
image processing means for extracting a feature amount of a target in the captured image and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
with
take the configuration.

Further, a program that is one embodiment of the present invention is
information processing equipment,
image processing means for extracting a feature amount of an object in a photographed image of an area before passage through a gate and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
to realize
take the configuration.

Further, an information processing method, which is one embodiment of the present invention, comprises:
extracting a feature amount of an object in a photographed image of an area before passing through a gate, and storing matching information relating to matching of the target based on the feature amount;
estimating a distance from the gate to an object in the captured image;
making a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
take the configuration.

ADVANTAGE OF THE INVENTION By being comprised as mentioned above, this invention can provide the information processing apparatus which can implement|achieve smooth passage of a gate.

It is a figure which shows the usage condition of the face authentication system in Embodiment 1 of this invention. 1 is a block diagram showing the configuration of a face authentication system according to Embodiment 1 of the present invention; FIG. FIG. 2 is a diagram showing an imaging situation by the face authentication system disclosed in FIG. 1; FIG. FIG. 2 is a diagram showing usage of the face authentication system disclosed in FIG. 1; 2 is a flowchart showing processing operations by the face authentication system disclosed in FIG. 1; 2 is a flowchart showing processing operations by the face authentication system disclosed in FIG. 1; It is a block diagram which shows the structure of the face authentication system in Embodiment 2 of this invention. FIG. 10 is a block diagram showing the configuration of an information processing system according to Embodiment 3 of the present invention; FIG. 11 is a block diagram showing the configuration of an information processing device according to Embodiment 3 of the present invention;

<Embodiment 1>
A first embodiment of the present invention will be described with reference to FIGS. 1 to 6. FIG. FIG. 1 is a diagram showing usage of a face authentication system. FIG. 2 is a diagram showing the configuration of a face authentication system. 3 to 6 are diagrams for explaining the processing operation of the face authentication system.

[overall structure]
A face authentication system 10 (information processing system) according to the present invention is a system used to restrict or manage entry and exit of a person (object) in a specific place such as an office or an event venue. For example, the imaging device C that constitutes the face authentication system 10 is installed near each gate that is opened and closed when a person enters or exits.

In the example shown in FIG. 1, a plurality of gates G are arranged in parallel and adjacent to each other, and people pass through in the direction indicated by the arrow from the right side of FIG. For this reason, the area on the right side of FIG. 1 with respect to each gate G is an area in front of the person passing through the gate (front area). In the area before passage of each gate G, lanes along which people who are going to pass through the gate G pass side by side are located in parallel corresponding to the respective gates G. As shown in FIG. Each lane may or may not be partitioned by some member. Also, in this embodiment, the case where a plurality of gates G are arranged adjacently is exemplified, but the number of gates G may be only one.

In the situation shown in FIG. 1, the imaging device C that constitutes the face authentication system 10 in this embodiment is installed near each corresponding gate G and on the right side of the person heading to each gate G. As shown in FIG. However, the installation position of the imaging device is not limited to the position shown in FIG. 1, and may be installed in any position such as the left side facing the gate or above the gate. The face authentication system 10 also includes a display device D in the vicinity of each imaging device C. FIG.

Then, the face authentication system 10 captures an image of a person heading to the gate G with the equipped imaging device C. Then, from the face image of the person appearing in the photographed image, it is collated whether or not the person is a pre-registered person, and if the collation is successful, the gate G is opened so that the person can pass through. The configuration of the face authentication system 10 will be described in detail below.

[Configuration of face authentication system]
The face authentication system 10 according to the present embodiment is an information processing device having an arithmetic device and a storage device integrally configured with an imaging device C (camera) and a display device D (display). To put it the other way around, the imaging device C is equipped with an information processing device having an arithmetic device and a storage device for performing face authentication processing, and a display device D. FIG. However, the face authentication system 10 is not necessarily limited to being configured integrally with the imaging device C and the display device D. FIG. For example, the imaging device C, the display device D, and the information processing device that processes the captured image may be configured as separate devices and installed at separate locations.

Specifically, as shown in FIG. 2, the face authentication system 10 includes an imaging device C and a display device D, and a feature amount extraction unit 11 constructed by an arithmetic device executing a program, and a distance measurement A unit 12 , a matching unit 13 , and a gate control unit 14 are provided. The face authentication system 10 also includes a feature quantity storage unit 15 and a matching data storage unit 16 built in a storage device.

The image pickup device C (image pickup means) includes a camera and a camera control unit for acquiring a photographed image of the front side area of the gate G, that is, the front gate area of the corresponding lane at a predetermined frame rate. As shown in FIG. 1, for example, the imaging apparatus C has an imaging area defined by the Ca line. For example, when there are three persons P10, P11, and P12 in the lane as shown in FIG. 1, the captured image captured by the imaging device C is as shown in FIG. 3(a). The photographed image is set so as to be generally in focus within a preset distance range with respect to the imaging device C in the perspective direction.

When the photographed image is captured by the imaging device C, the feature quantity extraction unit 11 (image processing means) extracts a person in the photographed image, and first performs processing for extracting the person's feature quantity. Specifically, the feature amount extraction unit 11 extracts persons in the captured image, targets all the extracted persons, and generates the feature amounts necessary for matching from the face regions of the persons. Note that the feature amount is information for later performing matching processing by calculating a matching score, for example, similarity to the feature amount of a person registered in advance in the matching data storage unit 16 in the matching unit 13 . Note that the feature amount may be a feature amount used in an existing face matching technique, or may be a feature amount calculated by another method.

Then, the feature amount extraction unit 11 stores the extracted feature amount in the feature amount storage unit 15 as information (matching information) used for matching of a person, that is, information related to person matching. At this time, the feature amount is stored in the feature amount storage unit 15 in association with information identifying the person in the captured image. A person in a captured image may be tracked in a subsequent captured image. In that case, the tracked person and the feature amount in the feature amount storage unit 15 are associated with each other.

Further, the feature amount extraction unit 11 may extract feature amounts from different photographed images for one person and store a plurality of feature amounts. Moreover, the feature amount extraction unit 11 may store only one feature amount when the feature amount is extracted from different photographed images. That is, if a feature amount is extracted each time a photographed image of the same person is acquired, only one feature amount may be updated and stored. For example, the quality of the extracted feature amounts may be determined, and only one feature amount with the highest quality may be stored in association with a person.

Note that the feature quantity extraction unit 11 may perform matching processing using a matching unit 13, which will be described later. In this case, the feature amount extraction unit 11 issues a matching instruction to the matching unit 13, and performs matching processing between the feature amount of the person in the captured image extracted as described above and the person registered in advance. Then, the feature amount extraction unit 11 may acquire the matching result from the matching unit 13 and store the matching result in the feature amount storage unit 15 as matching information related to person matching. At this time, the feature amount is stored in the feature amount storage unit 15 in association with information identifying the person in the captured image. A person in a captured image may be tracked in a subsequent captured image. In that case, the tracked person is associated with the matching result in the feature amount storage unit 15 . At this time, feature amount extraction and matching processing may be performed on a plurality of captured images, and in that case, only one matching result may be updated and stored in association with the person.

The distance measuring unit 12 (distance estimating means) measures the distance from the gate G to the person in the photographed image from which the feature amount is extracted as described above. At this time, in this embodiment, the distance from the gate G to the person is measured using the image portion of the person in the captured image. Specifically, the distance is measured as follows.

The distance measurement unit 12 first sets a reference value necessary for measuring the distance to the person in the captured image. Specifically, the distance measurement unit 12 extracts the image portion of the face area of the person to be processed from within the captured image. Extraction of a person's face area is performed, for example, by judging from the position, color, etc. with respect to the whole image of a moving person. Then, the distance measurement unit 12 performs an attribute analysis process for determining attributes of the person from the image portion of the face area. Here, the attributes of a person are, for example, sex, age (age, adult, child), race, and the like.

In the attribute analysis process, for example, attribute discrimination information, which is information necessary to discriminate attributes from the image portion of the face region, is extracted, and the extracted attribute discrimination information and pre-registered attribute discrimination reference information are combined. A person's attribute is determined by comparison. Here, the attribute discrimination information is, for example, information representing physical characteristics generally appearing in a person's face region for each attribute such as gender and age. Attribute analysis processing for determining attributes such as gender and age (age) of a person can be realized with existing technology, so detailed description of such processing will be omitted. Also, the distinguishable attribute is not limited to the attributes described above, and may be any attribute.

Then, the distance measurement unit 12 sets a reference value corresponding to the determined attribute of the person. Here, the reference value is registered in advance in a storage device installed in the face authentication system 10. For example, in the present embodiment, the reference value of the inter-eye distance representing the distance between the eyes of a person is set for each attribute. registered with. As an example, when a certain numerical value is registered as the distance between eyes, which is the reference value for an attribute such as "male", the distance between eyes, which is the reference value for an attribute such as "female", is smaller than the reference value for men. is set. Also, for example, if a certain numerical value is registered as the inter-eye distance, which is the reference value for the attribute "adult" age from 15 to 60 years old, the attribute reference for age under 15 "child" The inter-eye distance, which is the value, is set to a value smaller than the standard value for adults. In this way, the reference value is a value according to the general build of a person's attributes. Then, the distance measurement unit 12 sets a reference value registered corresponding to the attribute determined for the person extracted from the photographed image as the reference value of the person.

Furthermore, the distance measurement unit 12 measures the distance to the person using the reference value set for the person as described above. Specifically, the distance measurement unit 12 first detects the distance between the eyes of the person from the image portion of the face area of the person as the target information representing the characteristics of the person in the captured image. For example, as indicated by d10, d11, and d12 in FIG. 3B, the inter-eye distances of the persons P10, P11, and P12 in the captured image are detected. Then, the detected inter-eye distances d10, d11, d12 are compared with the reference values set for each person P10, P11, P12, and the distance from the gate G to each person is measured. For example, the distance from the gate G to the person is measured from the difference in the inter-eye distance detected from the person and the ratio of the difference with respect to the reference value set for the person. Note that the distance measurement unit 12 may measure the relative distance of the person in the captured image, that is, the order with respect to the gate G, as the distance with respect to the gate G.

Here, an example of distance measurement from the gate G to the persons P10, P11, P12 will be described. In the example of FIG. 1, the persons P10, P11, and P12 are arranged in order toward the gate G, and the captured image is taken as shown in FIG. 3(b). At this time, if the physiques and face sizes of the persons P10, P11, and P12 are substantially the same, the inter-eye distances d10, d11, and d12 of the persons P10, P11, and P12 are generally d10>d11>. d12. On the other hand, if the person P10 is a child and the persons P11 and P12 are adults, the face of a child is generally considered to be small and the distance between the eyes is short. d11>d12>d10. Under such circumstances, in the present embodiment, the attribute of the person P10 is determined to be "child", a small reference value is set, and the distance is measured using this reference value and the detected inter-eye distance d10. be. The attributes of the persons P11 and P12 are determined to be "adult", a reference value larger than that of a child is set, and the distance is measured using this reference value and the detected inter-eye distances d11 and d12. be done. As a result, as shown in FIG. 4, the distances D10, D11, and D12 to each person can be measured so that the persons P10, P11, and P12 are in the same order as the actual order with respect to the gate G.

By associating the measured distance with the person in the captured image, the distance measurement unit 12 associates the distance with the feature amount of the same person stored in the feature amount storage unit 15 . The person in the captured image may be tracked in the subsequent captured image. In that case, the distance to the tracked person is measured in the same manner as described above, and the distance associated with the person is updated. . It should be noted that the association of persons in captured images that change in time can be realized by tracking feature points or the like.

The method of detecting the inter-eye distance by the distance measuring unit 12 is not limited to the method described above, and any method may be used. Further, the distance measurement unit 12 may detect the size of other parts of the person or other characteristics as object information instead of the distance between the eyes, and measure the distance. In this case, the reference value described above also becomes a value corresponding to the target information.

Here, the distance measurement unit 12 is not necessarily limited to measuring the distance from the gate G to the person. For example, the distance measurement unit 12 may estimate the relative positional relationship between the persons with respect to the gate. As an example, the distance measurement unit 12 estimates the proximity of each person to the gate, that is, the perspective relationship between the persons with respect to the gate G, based on the above-described object information such as the distance between the eyes and the reference value. good.

The collation unit 13 (collation means) performs collation processing between the person in the photographed image and the person registered in advance. At this time, the matching unit 13 performs matching processing based on the distance to the person measured as described above. For example, the matching unit 13 determines that a person is located in a predetermined range located at a preset distance from a gate G that is set immediately before the gate G, and that person is located closest to the gate G in the captured image. If so, the matching process for the person is performed. Note that the collation unit 13 may perform collation processing for a person simply when the person is located within a predetermined range located at a preset distance from the gate G set immediately before the gate G. Alternatively, matching processing for a person may be performed based on other criteria according to the distance to the person. In addition, when the distance measurement unit 12 estimates only the relative positional relationship between the persons with respect to the gate G as described above, the matching unit 13 determines the person closest to the gate G from the positional relationship. A matching process may be performed.

The matching process by the matching unit 13 is performed using the feature amount stored in the feature amount storage unit 15 of the person who is the processing target based on the distance as described above. That is, the collation unit 13 does not generate a new feature amount from the face region of the person in the captured image, and compares the feature amount stored in the feature amount storage unit 15 with the feature amount registered in the collation data storage unit 16 in advance. A matching score, which is the degree of similarity between the person's feature quantity and the similarity, is calculated, and matching is performed by determining whether or not the matching score is higher than a threshold value. If the collation score is higher than the threshold value, the collation is considered successful, and it is determined that the person who is about to pass through the gate G is a pre-registered person. It should be noted that any collation method may be used.

Note that the matching unit 13 has already performed the matching process on the person to be processed based on the distance based on the instruction from the feature amount extraction unit 11 as described above, and the feature amount storage unit 15 stores the matching result. If it is stored, only the collation result is confirmed. That is, the collation unit 13 examines the success or failure of the collation result, which is the collation information stored for the person to be processed according to the distance, and determines whether or not the collation is successful.

The gate control unit 14 (gate control means) first determines whether or not a person can pass through the gate G based on the collation result of the collation unit 13 . Specifically, it is determined that a person for whom collation by the collating unit 13 is successful is passable. Further, the gate control unit 14 has a function of displaying on the display device D the result of collation, that is, the success or failure of the collation. Further, the gate control unit 14 also has a gate control function of opening and closing the gate G, and controls the gate G to be opened for a person determined to be able to pass through.

The display device D is arranged with its display surface facing the front area of the gate G so that a person who is about to pass through the gate G can see it. However, the display device D may not necessarily be provided.

[motion]
Next, the operation of the face authentication system 10 described above will be described with reference to the flow charts of FIGS. 5 and 6. FIG. Here, the operation of the face authentication system 10 corresponding to the gate G will be described, and the case where people are lined up for the gate G as shown in FIGS. 3 and 4 will be described as an example.

The imaging device C corresponding to the gate G continues to capture the image of the region on the front side of the gate G. Then, the face authentication system 10 always performs the following processing on the captured image.

First, the feature amount extraction unit 11 extracts persons (objects) P10, P11, and P12 to be processed from within the photographed image (step S1). Then, if the feature amount of the extracted person can be extracted from the situation of the captured image (Yes in step S2), the feature amount extraction unit 11 generates the feature amount necessary for matching from the face region of the person ( step S3). Then, the feature amount extraction unit 11 stores the extracted feature amount in the feature amount storage unit 15 in association with the person in the captured image. Note that if the captured image does not clearly show the face area of the person or the front of the face is not captured, or if the feature amount of the person cannot be sufficiently generated from the captured image (No in step S2). , the feature amount is generated for the subsequent captured image.

Subsequently, the distance measuring unit 12 measures the distance from the gate G to the person in the photographed image from which the feature amount has been extracted (step S4). Here, the process of measuring the distance by the distance measuring unit 12 will be described with reference to the flowchart of FIG.

The distance measurement unit 12 performs an attribute analysis process on the image portion of the person's face area in the captured image to determine the person's attribute. For example, in the examples of FIGS. 1 and 3, it is assumed that the attribute of the person P10 is determined to be child, and the attributes of the persons P11 and P12 are determined to be adults. Then, the distance measuring unit 12 sets a reference value stored in advance in the face authentication system 10 corresponding to the determined attribute of the person as the reference value of the person (step S11). For example, in the examples of FIGS. 3 and 4, a reference value corresponding to a child is set for the person P10, and a reference value corresponding to an adult is set to the persons P11 and P12.

Subsequently, the distance measurement unit 12 calculates the size of a predetermined part that is characteristic of the person as target information necessary for measuring the distance to the gate G of the person in the photographed image, here, the distance between the eyes of the person. is detected (step S12). For example, the inter-eye distances of the persons P10, P11 and P12 are detected as indicated by d10, d11 and d12 in FIG. 3(b).

Then, the distance measuring unit 12 compares the reference value set for each of the persons P10, P11, P12 as described above with the inter-eye distances d10, d11, d12 of each of the persons P10, P11, P12 for each person. Then, the distances from the gate G to each person P10, P11, P12 are measured (step S13). For example, in the example of FIG. 3B, the inter-eye distance d11 of the person P11 is the second from the gate among the three persons, but the reference values set for the persons P10, P11, and P12 are different. Therefore, the distances D10, D11, and D12 to each person are measured so that the order of the persons P10, P11, and P12 is the same as the actual order with respect to the gate G, as shown in FIG.

Subsequently, the matching unit 13 performs matching processing for each person based on the distance to each person P10, P11, P12 measured as described above. At this time, when the person is located at a preset distance from the gate G set immediately before the gate G, and the person is located closest to the gate G in the photographed image, the matching unit 13 Such person verification processing is performed (Yes in step S5, step S6). Therefore, in the example of FIG. 4, the person P10 closest to the gate G is collated. Specifically, the collation unit 13 compares the feature amount stored in the feature amount storage unit 15 in association with the person in the captured image to be collated, and the person registered in the collation data storage unit 16 in advance. This is performed by calculating a matching score, which is the degree of similarity between the feature amount and, and determining whether or not the matching score is higher than a threshold value (step S6). If the collation score is higher than the threshold value, the collation is considered successful (Yes in step S7), and it is determined that the person who is about to pass through the gate G is a pre-registered person.

As a result of the collation processing by the collation unit 13, when the person P10 positioned in front of the gate G is successfully collated (Yes in step S7), the gate control unit 14 permits the person P10 to pass through the gate G and opens the gate G. (step S8). At this time, the gate control unit 14 displays on the display device D whether or not the passage is permitted.

As described above, according to the face authentication system 10 of the present embodiment, the feature amount is extracted in advance from the face area of the person in the area before passing through the gate G, and the matching process is performed immediately before the gate. The gate can be properly opened and closed by As a result, smooth passage through the gate G by a person can be realized.

In addition, since the feature amount of the person is extracted and stored from the photographed image taken not only immediately before the gate G but also at any timing when the person is heading toward the gate G, it is possible to extract the feature amount with high reliability. Good matching can be done. As a result, smooth passage through the gate G by a person can be realized.

In the above, the case where the target who is about to pass through the gate G is a person is exemplified. For example, it may be an object such as luggage. Accordingly, the information used to measure the distance from the gate G, such as the reference value described above and the object information representing the characteristics of the object, may be information representing any characteristics that can be detected from the object. Moreover, any feature amount that can be detected from an object may be used when performing the matching process.

<Embodiment 2>
A second embodiment of the present invention will now be described with reference to FIG. FIG. 7 is a block diagram showing the configuration of the face authentication system.

The face authentication system 10 of this embodiment has almost the same configuration as that of the above-described first embodiment, but measures the distance from the gate G to the person without using the captured image for extracting the feature amount. This is the configuration. Configurations different from those of the first embodiment will be mainly described in detail below.

As shown in FIG. 7, the face authentication system 10 of this embodiment includes a distance measuring device E in addition to the face authentication system 10 described in the first embodiment. The distance measuring device E is, for example, an infrared depth sensor, and uses the measured depth, which is information different from the captured image for extracting the feature amount of the person, as described above. It is a device that can measure the distance to a person who does.

The distance measuring device E is, for example, near each corresponding gate G, and is installed on the right side or above the gate when viewed from the person heading to each gate G, similar to the imaging device C. Further, if the distance measuring device E is composed of one device, one unit is installed, and if it is composed of multiple units, a plurality of units is installed. Note that the distance measuring device E may be a device that measures the distance to the person by another method.

Then, the distance measurement unit 12 in this embodiment acquires the measured depth from the distance measuring device E and associates it with the person in the captured image. For example, the distance measuring unit 12 identifies the depth for each position in the area before passing the gate G, and associates it with the position of the captured image. Thereby, the distance to each person positioned in the captured image can be specified, and the distance can be associated with the person. In this manner, the measured distance can be associated with the feature amount of the same person stored in the feature amount storage unit 15, as in the first embodiment.

The person in the captured image may be tracked in the subsequent captured image. In that case, the distance to the tracked person is measured in the same manner as described above, and the distance associated with the person is updated. do. It should be noted that the association of persons in captured images that change in time can be realized by tracking feature points or the like.

Then, the collation unit 13 in this embodiment performs collation processing based on the distance to the person measured as described above. This collation processing is the same as in the first embodiment, and when a person is positioned in front of the gate G, the feature amount stored for the person is read out and collation processing is performed.

Here, the distance measuring device E and the distance measuring section 12 are not necessarily limited to measuring the distance from the gate G to the person. For example, the distance measuring device E and the distance measuring unit 12 may estimate the relative positional relationship between the persons with respect to the gate. That is, the distance measuring device E and the distance measuring unit 12 may estimate the perspective relationship between the person and the gate G. Then, the collation unit 13 may perform collation processing on the person closest to the gate G based on the estimated relative positional relationship between the persons with respect to the gate G. FIG.

Even in the above manner, the gate can be appropriately opened and closed for the person in front of the gate, and the person can pass through the gate G smoothly.

<Embodiment 3>
Next, a third embodiment of the invention will be described with reference to FIGS. 8 and 9. FIG. FIG. 8 is a block diagram showing the configuration of an information processing system according to the third embodiment. FIG. 9 is a block diagram showing the configuration of the information processing apparatus according to the third embodiment. It should be noted that this embodiment shows an outline of the configuration of the face authentication system described in the first and second embodiments.

As shown in FIG. 8, the information processing system 100 in this embodiment includes:
Imaging means 110 for acquiring a photographed image of a region before passing through the gate;
image processing means 120 for extracting a feature amount of a target in the captured image and storing matching information used for matching the target based on the feature amount;
distance estimation means 130 for estimating the distance from the gate to the object in the captured image;
A matching means 140 for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
with
take the configuration.

Further, in this embodiment, the imaging means 110 may be removed from the information processing system 100 shown in FIG.
That is, the information processing device 200 in this embodiment
An image processing means 220 for extracting a feature amount of an object in a photographed image of an area before passage through a gate and storing matching information used for matching the target based on the feature amount;
distance estimation means 230 for estimating the distance from the gate to the object in the captured image;
a matching means 240 for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
with
take the configuration.

Note that the image processing means 120, 220, the distance estimation means 130, 230, and the matching means 140, 240 described above may be constructed by an arithmetic unit executing a program, or may be constructed by an electronic circuit. can be anything.

Then, the information processing system 100 or the information processing device 200 configured as described above,
extracting a feature amount of an object in a photographed image obtained by photographing a region before passing through a gate, and storing matching information used for matching the target based on the feature amount;
estimating a distance from the gate to an object in the captured image;
making a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
It operates to perform the process of

According to the information processing system 100 or the information processing apparatus 200 described above, the feature amount is extracted in advance from the face area of the person in the area before passage through the gate, or the matching process is performed in advance using the feature amount. Since the matching determination is performed immediately before, the gate can be appropriately opened and closed for the person. In addition, since the feature amount of the person is extracted from the photographed image taken at an arbitrary timing when the person goes to the gate and is stored, the feature amount with high reliability can be extracted and collation can be performed with high accuracy. As a result, smooth passage through the gate by a person can be realized.

<Appendix>
Some or all of the above embodiments may also be described as the following appendices. An outline of the configuration of an information processing apparatus, an information processing system, a program, and an information processing method according to the present invention will be described below. However, the present invention is not limited to the following configurations.

(Appendix 1)
image processing means for extracting a feature amount of an object in a photographed image of an area before passage through a gate and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
Information processing device with

(Appendix 2)
The information processing device according to Supplementary Note 1,
Based on the estimated distance, the matching means performs a matching process between the feature amount, which is the stored matching information of the target for which the distance is estimated, and a pre-registered feature amount.
Information processing equipment.

(Appendix 3)
The information processing device according to appendix 2,
The matching means performs a matching process between the stored feature amount of the target located at a preset distance from the gate and a pre-registered feature amount.
Information processing equipment.

(Appendix 4)
The information processing device according to appendix 2 or 3,
The matching means performs a matching process between the stored feature quantity of the object located closest to the gate and a pre-registered feature quantity,
Information processing equipment.

(Appendix 5)
The information processing device according to Supplementary Note 1,
The image processing means performs matching processing between the stored feature amount and a pre-registered feature amount, and stores the matching result as the matching information,
The matching means performs a matching determination based on the estimated distance and a matching result, which is the stored matching information of the target for which the distance was estimated.
Information processing equipment.

(Appendix 6)
The information processing device according to any one of Appendices 1 to 5,
The image processing means extracts a feature amount of the target from a plurality of the captured images, and updates and stores the collation information of the target based on the feature amount.
Information processing equipment.

(Appendix 7)
The information processing device according to any one of Appendices 1 to 6,
The distance estimating means estimates a distance to an object existing in a region before passage of the gate using information different from the captured image for extracting the feature quantity.
Information processing equipment.

(Appendix 8)
The information processing device according to any one of Appendices 1 to 6,
The distance estimating means estimates the distance to the target using an image portion of the target in the captured image.
Information processing equipment.

(Appendix 9)
The information processing device according to appendix 8,
The distance estimating means determines an attribute of a target in the captured image, sets a reference value corresponding to the attribute, and uses the reference value to estimate a distance to the target in the captured image.
Information processing equipment.

(Appendix 10)
The information processing device according to appendix 9,
The distance estimating means detects target information representing characteristics of the target in the captured image, and estimates a distance to the target in the captured image based on the reference value and the target information.
Information processing equipment.

(Appendix 11)
The information processing device according to Appendix 10,
The distance estimating means detects a size of a predetermined part of the object in the photographed image as the object information, and measures the distance to the object in the photographed image based on the size of the predetermined part of the object with respect to the reference value. to estimate the distance,
Information processing equipment.

(Appendix 12)
an imaging means for acquiring a photographed image of the area before passing through the gate;
image processing means for extracting a feature amount of a target in the captured image and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
Information processing system with

(Appendix 12.1)
The information processing system according to Appendix 12,
The matching means performs a matching process between the stored feature amount of the target located at a preset distance from the gate and a pre-registered feature amount.
Information processing system.

(Appendix 12.2)
The information processing system according to Appendix 12 or 12.1,
The matching means performs a matching process between the stored feature quantity of the object located closest to the gate and a pre-registered feature quantity,
Information processing system.

(Appendix 13)
information processing equipment,
image processing means for extracting a feature amount of an object in a photographed image of an area before passage through a gate and storing matching information relating to matching of the target based on the feature amount;
distance estimating means for estimating a distance from the gate to an object in the captured image;
matching means for performing a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
program to make it happen.

(Appendix 13.1)
The program according to Appendix 13,
The matching means performs a matching process between the stored feature amount of the target located at a preset distance from the gate and a pre-registered feature amount.
program.

(Appendix 13.2)
The program according to Appendix 13 or 13.1,
The matching means performs a matching process between the stored feature quantity of the object located closest to the gate and a pre-registered feature quantity,
program.

(Appendix 14)
extracting a feature amount of an object in a photographed image of an area before passing through a gate, and storing matching information relating to matching of the target based on the feature amount;
estimating a distance from the gate to an object in the captured image;
making a matching determination based on the estimated distance and the stored matching information of the target for which the distance was estimated;
Information processing methods.

(Appendix 15)
The information processing method according to appendix 14,
Based on the estimated distance, matching processing is performed between the feature amount, which is the stored matching information of the target for which the distance is estimated, and a pre-registered feature amount.
Information processing methods.

(Appendix 16)
The information processing method according to appendix 15,
Performing a matching process between the stored feature amount of the target located at a preset distance from the gate and a pre-registered feature amount;
Information processing methods.

(Appendix 17)
The information processing method according to appendix 15 or 16,
Performing a matching process between the stored feature amount of the target located closest to the gate and a pre-registered feature amount,
Information processing methods.

(Appendix 18)
18. The information processing method according to any one of Appendices 15 to 17,
estimating a distance to an object existing in a region before passing through the gate using information different from the captured image for extracting the feature amount;
Information processing methods.

(Appendix 19)
18. The information processing method according to any one of Appendices 15 to 17,
estimating the distance to the target using the image portion of the target in the captured image;
Information processing methods.

(Appendix 19.1)
The information processing method according to Appendix 19,
determining an attribute of a target in the captured image, setting a reference value corresponding to the attribute, and estimating a distance to the target in the captured image using the reference value;
Information processing equipment.

(Appendix 19.2)
The information processing method according to Appendix 19.1,
Detecting target information representing characteristics of the target in the captured image, and estimating a distance to the target in the captured image based on the reference value and the target information;
Information processing methods.

(Appendix 19.3)
The information processing method according to Appendix 19.2,
Detecting a size of a predetermined part of the target in the photographed image as the target information, and estimating a distance to the target in the target image based on the size of the predetermined part of the target with respect to the reference value.
Information processing methods.

The program described above is stored in a storage device or recorded in a computer-readable recording medium. For example, the recording medium is a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

Although the present invention has been described with reference to the above-described embodiments and the like, the present invention is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

10 face authentication system 11 feature amount extraction unit 12 distance measurement unit 13 matching unit 14 gate control unit 15 feature amount storage unit 16 matching data storage unit 100 information processing system 200 information processing device 110 imaging means 120 and 220 image processing means 130 and 230 Distance estimating means 140, 240 Verification means C Imaging device D Display device E Distance measuring device G Gate

Claims (11)

an image processing means for extracting and storing a feature amount of an object in a photographed image obtained by photographing a region before passage through a gate;
For an object located within a predetermined range in the pre-passing area, a matching determination is made between the feature amount extracted and stored before the target is located in the predetermined range and the feature amount registered in advance. a matching means to perform;
Information processing system with The information processing system according to claim 1,
The image processing means extracts and stores feature amounts of a plurality of objects in the photographed image, performs collation processing between the extracted feature amounts and pre-registered feature amounts, and outputs the collation result as the Stored as matching information for the target,
The matching means compares an object located closest to the gate determined based on the positional relationship of the plurality of objects from which the feature amount is extracted in the photographed image, and the stored positional relationship of the object. Make a matching decision based on the matching result, which is the matching information
Information processing system. The information processing system according to claim 2,
The image processing means extracts a feature amount of the target from a plurality of the captured images, updates and stores the collation information of the target based on the feature amount,
Information processing system. The information processing system according to claim 2 or 3,
estimating means for estimating the positional relationship of the plurality of targets existing in the area before passage of the gate using information different from the captured image for extracting the feature amount,
Information processing system. The information processing system according to claim 2 or 3,
An estimating means for estimating the positional relationship of the plurality of targets using the image portion of the target in the captured image,
Information processing system. The information processing system according to claim 5,
The estimating means discriminates an attribute of the object in the captured image, sets a reference value for the image portion of the object corresponding to the attribute, and compares the reference value with the image portion of the object. estimating the positional relationship of the plurality of targets in the captured image;
Information processing system. The information processing system according to claim 6,
The estimating means detects target information representing characteristics of the target in the captured image, and estimates the positional relationship of the plurality of targets in the captured image based on the reference value and the target information.
Information processing system. The information processing system according to claim 7,
The estimating means detects a size of a predetermined portion of the object in the photographed image as the object information, and determines the plurality of objects in the photographed image based on the size of the predetermined portion of the object with respect to the reference value. Estimate the positional relationship of
Information processing system. an imaging means for acquiring a photographed image of the area before passing through the gate;
image processing means for extracting and storing a feature amount of a target in the captured image;
For an object located within a predetermined range in the pre-passing area, a matching determination is made between the feature amount extracted and stored before the target is located in the predetermined range and the feature amount registered in advance. a matching means to perform;
Information processing system with information processing equipment,
an image processing means for extracting and storing a feature amount of an object in a photographed image obtained by photographing a region before passage through a gate;
For an object located within a predetermined range in the pre-passing area, a matching determination is made between the feature amount extracted and stored before the target is located in the predetermined range and the feature amount registered in advance. a matching means to perform;
program to make it happen. Extracting and storing the feature amount of the object in the photographed image obtained by photographing the region before passing through the gate,
For an object located within a predetermined range in the pre-passing area, a matching determination is made between the feature amount extracted and stored before the target is located in the predetermined range and the feature amount registered in advance. conduct,
Information processing methods.

Images