Information processing device, display method, and program

Abstract

The objective of the invention is to provide an information processing device that achieves an improvement in the accuracy of search results. An information processing device (10) according to the present disclosure comprises: a management unit (11) that manages at least one object, an attribute to which the object is classified, and a reliability indicating the probability that the object exhibits the attribute, in association with one another; a calculation unit (12) that, by use of the reliability of an attribute designated as a search condition and the reliability being managed in association with an attribute identical with or similar to the attribute designated as the search condition, calculates a score indicating a matching degree of the object with respect to the search condition; and a display unit (13) that displays the object on the basis of the calculated score.

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, a display method, and a program. [Background technology]

[0002] In recent years, surveillance cameras have become widespread and are now installed in various locations. Images captured by surveillance cameras are used, for example, in the investigation of various cases. Specifically, police may search for a suspicious person from a huge amount of video using the person's purpose information.

[0003] Patent Document 1 discloses a configuration of an information processing device that searches for a target person according to search conditions in which attributes in categories such as gender, hair color, and clothing color are specified. The information processing device of Patent Document 1 is specified not only with the search conditions in which attributes are specified, but also with a degree of certainty that indicates the likelihood of satisfying the search conditions, and displays people who satisfy the search conditions and the degree of certainty. For example, when male is specified as the attribute and 90% is specified as the degree of certainty, the information processing device displays as search results people who have a degree of certainty of 90% or more that they are classified as "male." In other words, the information processing device does not display people who have a degree of certainty of being classified as "male" that is less than 90%. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2020 / 255307 Summary of the Invention [Problem to be solved by the invention]

[0005] The information processing device disclosed in Patent Document 1 uses the certainty of each attribute to narrow down the search results to be displayed. Therefore, for example, among the people displayed as having a certainty of 90% or more for being classified as a man, which is specified as an attribute, there may be people who clearly do not meet the certainty of the specified attributes for hair color, clothing color, etc. In this way, among the people displayed as search results, there may be people who are clearly different from the person who is the search target, so it is desirable to improve the accuracy of the search results in order to find the search target early.

[0006] An object of the present disclosure is to provide an information processing device, a display method, and a program capable of improving the accuracy of search results. [Means for solving the problem]

[0007] An information processing device according to a first aspect of the present disclosure includes a management unit that associates and manages at least one object, an attribute by which the object is classified, and a confidence level indicating the probability that the object has the attribute, a calculation unit that calculates a score indicating the degree of match of the object with the search conditions using the confidence level of the attribute specified as a search condition and the confidence level associated with an attribute that is identical to or similar to the attribute specified as the search condition and managed in association with the attribute, and a display unit that displays the object based on the calculated score.

[0008] A display method according to a second aspect of the present disclosure manages at least one object, an attribute into which the object is classified, and a confidence level indicating the probability that the object has the attribute in association with each other, calculates a score indicating the degree of match of the object to the search criteria using the confidence level of the attribute specified as a search criterion and a confidence level associated with an attribute that is identical to or similar to the attribute specified as the search criterion, and displays the object based on the calculated score.

[0009] A program according to a third aspect of the present disclosure causes a computer to manage at least one object, an attribute into which the object is classified, and a certainty indicating the probability that the object has the attribute in association with each other, calculate a score indicating the degree of match of the object to the search conditions using the certainty of the attribute specified as a search condition and the certainty managed in association with an attribute that is identical to or similar to the attribute specified as the search condition, and display the object based on the calculated score. Effect of the Invention

[0010] The present disclosure makes it possible to provide an information processing device, a display method, and a program capable of improving the accuracy of search results. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a configuration diagram of an information processing device according to a first embodiment. [Diagram 2] FIG. 11 is a configuration diagram of an information processing device according to a second embodiment. [Diagram 3] FIG. 11 is a diagram illustrating data managed by a management unit according to the second embodiment. [Figure 4] FIG. 11 is a diagram showing a screen image displayed by a display unit according to the second embodiment. [Diagram 5] FIG. 11 is a diagram for explaining an overall confidence factor according to the second embodiment. [Figure 6] FIG. 11 is a diagram for explaining an overall confidence factor according to the second embodiment. [Figure 7] FIG. 11 is a diagram for explaining an overall confidence factor according to the second embodiment. [Figure 8] FIG. 11 is a diagram showing a flow of a display process of a search result according to the second embodiment. [Figure 9] FIG. 11 is a diagram showing a flow of display processing of a search condition designation area according to the second embodiment. [Figure 10] FIG. 11 is a diagram showing a screen image displayed by a display unit according to the second embodiment. [Figure 11]FIG. 2 is a configuration diagram of an information processing device according to each embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] (Embodiment 1) Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. A configuration example of an information processing device 10 according to the first embodiment will be described with reference to Fig. 1. The information processing device 10 may be a computer device that operates by a processor executing a program stored in a memory.

[0013] The information processing device 10 has a management unit 11, a calculation unit 12, and a display unit 13. The management unit 11, the calculation unit 12, and the display unit 13 may be software or modules that perform processing by a processor executing a program stored in a memory. Alternatively, the management unit 11, the calculation unit 12, and the display unit 13 may be hardware such as a circuit or a chip.

[0014] The management unit 11 manages at least one object, an attribute into which the object is classified, and a confidence level indicating the probability that the object has the attribute in association with each other. The object may be a person, an animal, a building, a structure, etc. Or, the object may be a means of transportation such as a car, a bicycle, a train, etc.

[0015] The attributes by which the object is classified may be properties classified within categories such as gender, age, and clothing color. For example, in the gender category, male and female may be used as attributes. In the age category, age groups such as teens, twenties, and thirties may be used as attributes, or age may be used. In the clothing color category, colors such as red, blue, and yellow may be used. In the clothing color category, the same color may be further classified, for example, bright red, deep red, and the like.

[0016] The degree of certainty indicates the probability that the object has the attribute, or in other words, the degree of certainty indicates the likelihood that the object has the specified attribute. The degree of certainty may be indicated, for example, as a percentage (%) or may be indicated using a decimal number that is equal to or greater than 0 and equal to or less than 1. When the degree of certainty is indicated using a decimal number that is equal to or greater than 0 and equal to or less than 1, the degree of certainty increases as the value increases.

[0017] The management unit 11 may hold a database that associates an attribute by which an object is classified with a confidence level that indicates the probability that the object has that attribute.

[0018] The calculation unit 12 calculates a score indicating the degree of matching of the object with the search conditions by using the confidence level of the attribute specified as the search condition and the confidence level associated with an attribute identical or similar to the attribute specified as the search condition and managed. The search conditions may be input by, for example, a user of the information processing device 10. Alternatively, the search conditions may be input to the information processing device 10 from another computer device via a network. Alternatively, the information processing device 10 may determine the search conditions by analyzing voice, text, images, or the like.

[0019] The certainty factors associated with attributes identical or similar to the attribute specified as the search condition are managed in the management unit 11. That is, the calculation unit 12 uses the attribute specified as the search condition to extract, from the database held by the management unit 11, the certainty factors associated with the attribute identical or similar to the attribute specified as the search condition.

[0020] The score indicating the degree of matching of the object to the search conditions may be determined such that the larger the value, the higher the degree of matching of the object to the search conditions. For example, when multiple attributes and their certainties are specified as search conditions, the calculation unit 12 may calculate an overall score for the object by summing the score values ​​calculated for each attribute. In other words, the score for the object is a value obtained by taking into account multiple attributes or combining multiple attributes.

[0021] For example, the display unit 13 may display a predetermined number of objects in descending order of score, or may display objects having scores exceeding a predetermined score threshold.

[0022] As described above, the information processing device 10 displays objects that match the search conditions highly as search results. This allows the user of the information processing device 10 to easily specify a desired object from the search results displayed on the information processing device 10.

[0023] 1, the configuration in which the management unit 11 is included in the information processing device 10 has been described, but for example, the management unit 11 may be included in a device different from the information processing device 10. In this case, the calculation unit 12 of the information processing device 10 may acquire information managed by the management unit 11 included in the other device via a network.

[0024] (Embodiment 2) Next, a configuration example of the information processing device 20 according to the second embodiment will be described with reference to Fig. 2. The information processing device 20 has a configuration in which a search condition acquisition unit 21 is added to the information processing device 10. The management unit 11, the calculation unit 12, and the display unit 13 constituting the information processing device 20 are similar to those of the information processing device 10, and therefore detailed description thereof will be omitted. In the following, functions, operations, etc. of the information processing device 20 that are different from those of the information processing device 10, or detailed functions, operations, etc. of the information processing device 20 and the information processing device 10 will be described.

[0025] The search condition acquisition unit 21 acquires search conditions. For example, the search condition acquisition unit 21 may acquire search conditions input by a user of the information processing device 20 via an input interface or the like. The user may input attributes and confidence levels by performing text input or voice input using, for example, a keyboard, a touch panel, a microphone, or the like. For example, when a user inputs search conditions, a witness to a person to be searched for may determine confidence levels, which are attributes by which the person to be searched for is classified. In this case, the search conditions to be input are determined according to the subjective opinion of the witness.

[0026] Alternatively, the search condition acquisition unit 21 may specify search conditions using an input image. For example, when a user searches for or retrieves a person, the user inputs image data showing the person to the information processing device 20. The search condition acquisition unit 21 may specify attributes of the person displayed in the image by performing image analysis processing or image recognition processing on the input image data, and further calculate the certainty of the attributes.

[0027] The image analysis process or image recognition process may be executed using a learning model generated to learn attributes related to people and confidence levels indicating the probability that a person has the attributes, using multiple image data showing a person as training data. The search condition acquisition unit 21 acquires the attributes of the person displayed in the image and the confidence levels indicating the probability that the person has the attributes by applying the input image data to the generated learning model.

[0028] Next, the data managed by the management unit 11 will be described with reference to FIG. 3. FIG. 3 shows that the database uses people as objects and manages the attributes of people. h_1 to h_4 shown in the person column are identification information for identifying people. For example, the attribute of male or female is set in the gender category. For example, ages such as 30s, 40s, and 50s are set in the age category. For example, colors such as bright red, deep red, chestnut, and navy blue are set in the clothing color category. For the glasses category, Yes is set if the person wears glasses, and No is set if the person does not wear glasses. The numerical value shown next to each attribute indicates the confidence level indicating the probability that each person has that attribute. In addition, the clothing color category may be divided into the color of the clothes of the upper body, the color of the clothes of the lower body, the color of the hat, the color of the shoes, and the like. An attribute and confidence level may be set for each of the color of the clothes of the upper body, the color of the clothes of the lower body, the color of the hat, and the color of the shoes.

[0029] As shown in FIG. 3, for example, the certainty factor of a person h_1 being male is 0.7, the certainty factor of a person being in their 30s is 0.8, the certainty factor of a person being in bright red clothing is 0.9, and the certainty factor of a person not wearing glasses is 0.9. Similarly, attributes and certainty factors are associated with each other for other people. The certainty factor expressed using a decimal point less than 1 indicates a higher certainty factor as the value increases. For example, with respect to the person h_1, it may be rephrased that there is a 70 percent probability that the person is male and an 80% probability that the person is in their 30s.

[0030] Here, the persons h_1 to h_4 are persons appearing in a video or the like captured by a surveillance camera. For example, the management unit 11 may acquire video data captured by a surveillance camera, and identify a plurality of persons, attributes related to the persons, and the certainty of the attributes from the video data. Specifically, the management unit 11 may acquire the attributes of the persons included in the video and the certainty indicating the probability that the person has the attribute, by applying the video data to a learning model, similar to the search condition acquisition unit 21. Furthermore, the management unit 11 may manage the video in which each person appears in the form of a still image or a video. The management unit 11 may manage the video in which each person appears in association with the attributes and certainty of each person appearing in the video. Furthermore, the management unit 11 may manage the frame images constituting the video in which each person appears in association with the attributes and certainty of each person appearing in the frame image. For example, when the person h_1 is designated, the management unit 11 may extract still image data in which the person h_1 appears.

[0031] Alternatively, a computer device other than the information processing device 20 may execute an analysis process of video data captured by a surveillance camera, and identify the attributes of a person included in the video data and a certainty factor indicating the probability that the person has the attribute. In this case, the management unit 11 may acquire the attributes of a person included in the video data and a certainty factor indicating the probability that the person has the attribute, via a network, from the computer device that analyzed the video data. Alternatively, a user of the information processing device 20 may input the analysis results of the computer device that analyzed the video data to the information processing device 20. The management unit 11 may also acquire video data in which a person is captured, from the computer device that analyzed the video data.

[0032] Next, a screen image displayed by the display unit 13 will be described with reference to FIG. 4. FIG. 4 shows a display screen 30. The display screen 30 has a search condition designation area 32 and a result display area 34. For example, a user of the information processing device 20 sets attributes and confidence in the search condition designation area 32. FIG. 4 shows that the user of the information processing device 20 has set male and 30s as attributes, and further shows that the confidence of male and the confidence of 30s are set using a slide bar in which a numerical value from 0 to 1 is set. For example, the user sets the attributes and confidence of a person to be searched for according to instructions from a witness who witnessed the person to be searched for. In addition, when a search condition is specified using an input image, the input image may be displayed in the search condition designation area 32. In this case, the confidence of each attribute is set based on the input image.

[0033] The search results based on the search criteria set in the search criteria specification area 32 are displayed in the result display area 34. The searched people and their scores for the search criteria may be displayed in the result display area 34. Also, #1 to #4 in the result display area 34 indicate rankings, with #1 being the person with the highest score for the search criteria.

[0034] As shown in Fig. 4, the search condition designation area 32 and the result display area 34 may be displayed simultaneously on one display screen 30. For example, when a user of the information processing device 20 changes an attribute or a confidence level in the search condition designation area 32, the order of the people displayed in the result display area 34 changes in response to the change operation. In this way, by displaying the search condition designation area 32 and the result display area 34 simultaneously, the user of the information processing device 20 can easily confirm the order of the people in the result display area 34 that changes in response to a change in the search conditions. Also, when there are a large number of people to be displayed in the result display area 34, all the people to be displayed may be displayed by performing a scroll operation or the like.

[0035] Furthermore, the confidence of all attributes may be set at once using a slide bar (not shown) of the overall confidence. For example, when 0.8 is specified on the slide bar of the overall confidence, the confidence of all attributes may be set to 0.8. Alternatively, as shown in FIG. 4, the overall confidence may be set using a polygonal or circular figure. Here, an example of setting the overall confidence using a polygonal or circular figure will be described with reference to FIG. 5 to FIG. 7. FIG. 5 to FIG. 7 show variations of figures used for setting the overall confidence. For example, a triangle, a pentagon, or a circle may be used for setting the overall confidence, as shown in FIG. 5 to FIG. 7. The vertices of the triangle and pentagonal figures are associated with the attributes. Points associated with the attributes are also shown on the circumference of the circle. When the number of attributes to be set is 3, the overall confidence may be set using a triangular figure. When the number of attributes to be set is 5, the overall confidence may be set using a pentagonal figure. When the number of attributes to be set is 5 or more, the overall confidence may be set using a circular figure. Alternatively, if the number of attributes to be set is four, a rectangle may be used, and the polygon to be used may be determined according to the number of attributes to be set.

[0036] FIG. 5 shows that the overall certainty is set to 0.8, and the certainty of each attribute is set to 0.8. The same shape figures shown inside each figure indicate the overall certainty. Since the certainty values ​​of each attribute are all the same, the figures showing the overall certainty are an equilateral triangle, a regular pentagon, and a perfect circle, respectively. Furthermore, when the overall certainty is 1, the figures showing the overall certainty coincide with the outermost solid lines of each figure. For example, the overall certainty may be determined by a user specifying an arbitrary position inside the figure.

[0037] Figure 6 shows that the overall confidence level was changed from 0.8 to 0.6 by moving any point on the side of each figure, except for the vertices, inward. The dotted lines inside each figure in Figure 6 show the overall confidence level before the change, and the solid lines inside the dotted lines show the overall confidence level after the change. Figure 6 shows that the confidence levels of all attributes have been changed to 0.6.

[0038] FIG. 7 shows that the certainty of each attribute is changed by moving the vertices of each figure inward. For example, in a triangular figure, it is shown that only the certainty of the attribute of 30s is changed from 0.8 to 0.6 by moving the vertex associated with the attribute 30s. Furthermore, in a pentagonal figure, it is shown that only the certainty that the color of the clothes is red is changed from 0.8 to 0.6 by moving the vertex associated with red as the color of the clothes. Furthermore, in a circular figure, it is shown that only the certainty that the color of the clothes is red is changed from 0.8 to 0.6 by moving the point on the circumference associated with red as the color of the clothes. Moreover, in each figure, the certainty of two or more attributes may be changed. In this way, it is possible to set the overall certainty using a polygon or a circle, and further adjust the certainty of each attribute.

[0039] Next, a description will be given of a score calculation process executed by the calculation unit 12. The calculation unit 12 calculates a score for each person managed by the management unit 11 using the following formula 1.

[0040] TIFF0007622849000001.tif8115

[0041] p j q : Confidence of the jth attribute of the search condition (query condition) p j h : Confidence of the jth attribute to be searched Sim(f j q,f j h ): Similarity between the jth attribute of the search criteria and the jth attribute of the search target

[0042] The jth attribute of the search criteria is, for example, an attribute set in the jth category displayed in the search criteria designation area 32 in Fig. 4. In Fig. 4, categories are counted in order from the top. For example, in Fig. 4, male set in the first category is the first attribute, and 30s set in the second category is the second attribute.

[0043] The jth attribute to be searched is, for example, an attribute set in the jth category shown in the database of Fig. 3. In Fig. 3, the categories are counted in order from the left excluding people. For example, in Fig. 3, the attribute set in the gender category is the first attribute, the attribute set in the age category is the second attribute, the attribute set in the clothing color category is the third attribute, and the attribute set in the glasses category is the fourth attribute.

[0044] The order of categories displayed in the search condition designation area of ​​Fig. 4 and the order of categories shown in the database of Fig. 3 may be predetermined so that the same categories are set in the same order. In other words, the first category displayed in the search condition designation area of ​​Fig. 4 and the first category excluding the person category shown in the database of Fig. 3 may be predetermined as a gender category.

[0045] Sim(f j q ,f j h ) may be, for example, an existing similarity function or may be predefined by a user. For example, similarity values ​​may be set for all combinations of attributes that can be set to the same category, such as Sim(male, male) = 1.0, Sim(red, true red) = 0.95, Sim(red, deep red) = 0.70. A similarity value of 1.0 indicates that the attributes match, and the smaller the value from 1.0, the lower the similarity between the two attributes becomes.

[0046] Also, Sim(f j q ,f j h ) calculates the similarity between the j-th attribute of the search criteria and the j-th attribute of the search target, and the similarity of attributes set in different categories does not have to be calculated. In other words, the similarity of Sim (male, navy blue) is not calculated. Alternatively, the similarity of attributes set in different categories may be set to a low value. Also, even if two attributes are able to be set in the same category, if they clearly do not have similarity, the similarity does not have to be calculated. For example, the similarity of Sim (30s, 50s) does not have to be calculated. Alternatively, the similarity of two attributes that are able to be set in the same category but clearly do not have similarity may be set to a low value.

[0047] For example, assume that (male, 0.9), (30s, 0.8), (40s, 0.2), and (red, 0.7) are entered as search conditions in the search condition specification area 32 in Fig. 4. The left side of the parentheses indicates the attribute, and the right side indicates the confidence level. Also, in Fig. 4, for example, only 30s is specified in the age category, but multiple age groups may be set.

[0048] In this case, the scores of people h_1 to h_4 managed in Figure 3 are calculated as follows:

[0049] S(h1) = 0.9 x 0.7 x Sim(male, male) + 0.8 x 0.8 x Sim(30s, 30s) + 0.7 x 0.9 x Sim(red, true red) = 0.9 x 0.7 x 1.0 + 0.8 x 0.8 x 1.0 + 0.7 x 0.9 x 0.95 = 1.8685

[0050] S(h2) = 0.9 x 0.9 x Sim(male, female) + 0.8 x 0.6 x Sim(30s, 30s) + 0.7 x 0.9 x Sim(red, deep red) = 0.9 x 0.9 x 0.0 + 0.8 x 0.6 x 1.0 + 0.7 x 0.9 x 0.7 = 0.921

[0051] S(h3)=0.9×0.9×Sim(male, male)+0.2×0.8×Sim(40s, 40s)+0.7×0.7×Sim(red, maroon)=0.9×0.9×1.0+0.2×0.8×1.0+0.7×0.7×0.8=1.362

[0052] S(h4) = 0.9 x 0.8 x Sim(male, male) + 0.7 x 0.6 x Sim(red, navy blue) = 0.9 x 0.8 x 1.0 + 0.7 x 0.6 x 0.0 = 0.72

[0053] The scores of the people h_1 to h_4 are, in descending order of score, h_1, h_3, h_2, and h_4. Thus, the display unit 13 displays in the result display area 34 in the order of h_1, h_3, h_2, and h_4.

[0054] Next, the flow of the display process of the search results according to the second embodiment will be described with reference to FIG. 8. Here, it is assumed that before the flow of the display process of the search results shown in FIG. 8 is started, the management unit 11 specifies the attributes of the multiple people displayed in the video data captured by the surveillance camera and the certainty of the attributes. For example, the management unit 11 may specify the attributes of the multiple people displayed in the video data and the certainty of the attributes by acquiring the video data captured by the surveillance camera and performing image analysis or the like on the acquired video data. Alternatively, the management unit 11 may receive the attributes of the multiple people displayed in the video data specified in another device and the certainty of the attributes via a network or the like. For example, the surveillance camera may specify the attributes of the multiple people displayed in the video data and the certainty of the attributes. In this case, the management unit 11 may receive the video data, the attributes, and the certainty from the surveillance camera via a network.

[0055] First, the search condition acquisition unit 21 acquires search conditions (S21). Specifically, the search condition acquisition unit 21 acquires attributes related to the search target and a confidence level indicating the probability of the attributes as search conditions. The search condition acquisition unit 21 may acquire search conditions input by the user of the information processing device 20 via an input interface, or may acquire attributes and confidence levels of a person to be searched identified by analyzing an image in which the person to be searched is displayed. For example, the image in which the person to be searched is displayed may be specified or input by the user of the information processing device 20.

[0056] Next, the calculation unit 12 calculates a score of the object of the search using the attributes and the confidence factor included in the search conditions (S22). Specifically, the calculation unit 12 calculates a score of each person using the attributes and the confidence factor included in the search conditions and the attributes and the confidence factor associated with each person managed in the management unit 11.

[0057] Next, the display unit 13 determines the objects to be displayed based on the scores calculated by the calculation unit 12 (S23). For example, when the number of people to be displayed is predetermined, the display unit 13 selects the predetermined number of people in descending order of the people with the highest scores. Alternatively, the display unit 13 may select people with scores higher than the predetermined score.

[0058] Next, the display unit 13 displays the selected object (S24). Specifically, the display unit 13 displays an image of the person selected based on the score in the result display area 34. The search condition acquisition unit 21 may set, as new search conditions, attributes and the certainty of the attributes associated with a person designated or selected by the user from among the people displayed in the result display area 34, and execute the processes from step S21 onward.

[0059] In addition, the result display area 34 may display the results of a search performed based on the confidence level for each attribute of a person specified as a search condition and the attributes of people appearing in images managed by the management unit 11.

[0060] As described above, the information processing device 20 according to the second embodiment calculates a score for each person using the search criteria and the attributes and certainty of each person managed in the management unit 11. Furthermore, the information processing device 20 identifies a person to be displayed in the result display area 34 based on the score. The information processing device 20 calculates a higher score as the certainty of the attribute managed in the management unit 11 increases. Furthermore, the information processing device 20 calculates a higher score as the similarity between the attribute input as the search criteria and the attribute managed in the management unit 11 increases. This allows the information processing device 20 to preferentially display in the result display area 34 people who match the search criteria more closely.

[0061] (Embodiment 3) Next, a flow of display processing of the search condition designation area 32 according to the third embodiment will be described with reference to Fig. 9. A user who uses the information processing device 20 may repeatedly change the certainty of the attributes that are search conditions and check the search results displayed in the result display area 34. For example, a person who has witnessed a suspicious person may check the search results displayed in the result display area 34 together with the person who has witnessed a suspicious person and search for an image in which the suspicious person appears. In such a case, if the suspicious person remembered by the person who has witnessed the suspicious person is not displayed in the search results, the search results displayed in the result display area 34 may be changed by repeatedly changing the certainty of the attributes that are search conditions.

[0062] The flow of the display process of the search condition designation area 32 shown in FIG. 9 is executed in order to reduce the number of times the certainty factor is changed and to enable efficient searching of people who are the subject of the search.

[0063] Steps S31 to S32 in Fig. 9 are similar to steps S21 to S22 in Fig. 8, and therefore detailed description thereof will be omitted. Next, the calculation unit 12 accepts a change in the certainty factor (S33). In other words, the calculation unit 12 acquires a certainty factor having a value different from the certainty factor included in the search conditions used to calculate the score in step S32.

[0064] Next, the calculation unit 12 calculates the score of the object using the changed certainty factor (S34). Specifically, the calculation unit 12 calculates the score of each person managed by the management unit 11 using the changed certainty factor.

[0065] Next, the calculation unit 12 judges whether the ranking will change when comparing the ranking based on the score calculated in step S32 with the ranking based on the score calculated in step S34 (S35). When the calculation unit 12 judges that the ranking will not change, it repeats the processes from step S33 onwards. Here, when repeating the process of step S33, the calculation unit 12 may, for example, increase the value of the confidence by a predetermined increment. For example, when the confidence is expressed using a decimal number from 0 to 1, the calculation unit 12 may increase or decrease the confidence by 0.1 each time the process of step S33 is repeated. In this way, the calculation unit 12 repeats changing the confidence until the ranking changes due to a change in the score.

[0066] When it is determined in step S35 that the ranking has changed, the calculation unit 12 specifies the value of the confidence level after the change in step S33 as a threshold value (S36). Next, the display unit 13 displays the threshold value in the search condition specification area 32 (S37). For example, the display unit 13 may display the threshold value using a vertical dotted line as shown in the confidence level slide bar associated with the gender category in the search condition specification area 32 of FIG. 10. Also, while FIG. 10 shows the threshold value when the input confidence level is increased, the display unit 13 may specify and display the threshold value when the input confidence level is decreased. The calculation unit 12 may specify a plurality of confidence level threshold values. In that case, the display unit 13 displays a plurality of threshold values ​​in the search condition specification area 32. Specifically, the display unit 13 may display both the threshold value when the input confidence level is increased and the threshold value when the input confidence level is decreased in the confidence level slide bar in the search condition specification area 32. Furthermore, the calculation unit 12 may specify a threshold value of a certain attribute, for example, a threshold value of a certainty factor associated with a gender category in step S36, and then specify a threshold value of a certainty factor associated with an age category. That is, the calculation unit 12 may specify threshold values ​​of certainty factors for two or more attributes among the attributes included in the search criteria.

[0067] Furthermore, the search condition acquisition unit 21 may set, as new search conditions, an attribute associated with a person specified by the user from among the people displayed in the search condition designation area 32 and the certainty factor of the attribute.

[0068] As described above, by displaying the certainty threshold value by the display unit 13, the user of the information processing device 20 can efficiently change the certainty factor when repeatedly changing the certainty factor of an attribute that is a search condition. In other words, the user can grasp the value of the certainty factor at which a change in ranking occurs by checking the threshold value displayed in the search condition designation area 32. Therefore, the user does not need to change the certainty factor to a range that does not cause a change in ranking, and can reduce the number of times the certainty factor of an attribute is changed.

[0069] FIG. 11 is a block diagram showing a configuration example of an information processing device 10 and an information processing device 20 (hereinafter, referred to as information processing device 10, etc.). Referring to FIG. 11, the information processing device 10, etc. includes a network interface 1201, a processor 1202, and a memory 1203. The network interface 1201 may be used to communicate with a network node (e.g., eNB, MME, P-GW, etc.). The network interface 1201 may include, for example, a network interface card (NIC) conforming to the IEEE 802.3 series. Here, eNB stands for evolved Node B, MME stands for Mobility Management Entity, and P-GW stands for Packet Data Network Gateway. IEEE stands for Institute of Electrical and Electronics Engineers.

[0070] The processor 1202 reads out and executes software (computer programs) from the memory 1203 to perform the processing of the information processing device 10 and the like described using the flowcharts in the above-mentioned embodiments. The processor 1202 may be, for example, a microprocessor, an MPU, or a CPU. The processor 1202 may include multiple processors.

[0071] The memory 1203 is configured by a combination of volatile memory and non-volatile memory. The memory 1203 may include storage located away from the processor 1202. In this case, the processor 1202 may access the memory 1203 via an I / O (Input / Output) interface (not shown).

[0072] 11, the memory 1203 is used to store a group of software modules. The processor 1202 reads out and executes the group of software modules from the memory 1203, thereby performing the processing of the information processing device 10 and the like described in the above-mentioned embodiment.

[0073] As described with reference to FIG. 11, each of the processors of the information processing device 10 in the above-described embodiment executes one or more programs including a set of instructions for causing a computer to execute the algorithm described with reference to the drawings.

[0074] In the above examples, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray® disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, the transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0075] The present disclosure is not limited to the above-described embodiment, and can be modified as appropriate without departing from the spirit and scope of the present disclosure.

[0076] A part or all of the above-described embodiments can be described as, but is not limited to, the following supplementary notes. (Appendix 1) A management unit that manages at least one object, an attribute to which the object is classified, and a confidence level indicating a probability that the object has the attribute in association with each other; a calculation unit that calculates a score indicating a degree of matching of the object with the search criteria using a certainty of an attribute specified as a search criteria and a certainty associated with an attribute that is the same as or similar to the attribute specified as the search criteria and managed; A display unit that displays the object based on the calculated score. (Appendix 2) The display unit is 2. The information processing device of claim 1, further comprising: a display unit for displaying the objects in descending order of the score. (Appendix 3) The display unit is 3. The information processing device according to claim 1, further comprising: a search condition designation area for displaying the search conditions; and a result display area for displaying the object. (Appendix 4) The display unit is 4. The information processing device according to claim 3, wherein a search condition designation area for displaying the search conditions and a result display area for displaying the object are displayed on the same screen. (Appendix 5) The calculation unit is 5. The information processing device according to claim 1, wherein the score is calculated so that the score increases as the certainty factor associated with and managed in association with an attribute that is identical to or similar to the attribute specified as the search condition increases. (Appendix 6) The calculation unit is The information processing device according to any one of claims 1 to 5, further comprising: calculating a score that increases as a degree of similarity between an attribute similar to the attribute specified as the search condition increases. (Appendix 7) An image analysis unit that analyzes the image to identify attributes of people included in the image and certainty of the attributes, The calculation unit is 7. The information processing device according to claim 1, wherein attributes of the identified person and a certainty of the attributes are used as the search conditions. (Appendix 8) The calculation unit is changing a certainty value of the attribute specified as the search condition and recalculating the score, and if the ranking of the scores of two or more of the objects before changing the certainty value of the attribute specified as the search condition changes due to the recalculation of the score, specifying the changed certainty value as a threshold value; The display unit is 8. The information processing device according to claim 1, further comprising: a display unit configured to display the threshold together with a degree of certainty of an attribute specified as the search condition. (Appendix 9) The calculation unit is 9. The information processing device according to claim 8, further comprising: changing a certainty value of an attribute specified as the search condition, recalculating the score, and, if a ranking of the scores of two or more of the objects before changing the certainty value of the attribute specified as the search condition does not change due to the recalculation of the score, changing the certainty value of the attribute specified as the search condition until the ranking changes. (Appendix 10) a management means for managing at least one image of a person; A reception means for receiving, as a search condition, a degree of certainty indicating the degree of certainty of each attribute of a person; a search means for executing a search for the image based on the specified confidence level and attributes of a person appearing in the image; a display means for displaying the image based on the result of the search; An information processing device comprising: (Appendix 11) managing at least one object, an attribute to which the object is classified, and a confidence level indicating a probability that the object has the attribute in association with each other; calculating a score indicating a degree of match of the object with respect to the search criteria using a certainty of the attribute specified as the search criteria and a certainty associated with an attribute identical or similar to the attribute specified as the search criteria and managed; A display method, comprising: displaying the object based on the calculated score. (Appendix 12) managing at least one object, an attribute to which the object is classified, and a confidence level indicating a probability that the object has the attribute in association with each other; calculating a score indicating a degree of match of the object with respect to the search criteria using a certainty of the attribute specified as the search criteria and a certainty associated with an attribute identical or similar to the attribute specified as the search criteria and managed; A non-transitory computer-readable medium having stored thereon a program that causes a computer to display the object based on the calculated score. [Explanation of symbols]

[0077] 10. Information processing device 11 Management Department 12 Calculation section 13 Display section 20 Information processing device 21 Search condition acquisition section 30 display screen 32 Search Criteria Specification Area 34 Results display area

Claims

1. A management means for managing at least one object, an attribute into which the object is classified, and a confidence level indicating a probability that the object has the attribute in association with each other; a calculation means for calculating a score indicating a degree of matching of the object with the search criteria using a certainty of an attribute designated as a search criteria and a certainty associated with an attribute identical or similar to the attribute designated as the search criteria and managed by the same; and a display means for displaying the object based on the calculated score.

2. The display means includes: The information processing device according to claim 1 , wherein the objects are displayed in descending order of the score.

3. The display means includes: The information processing apparatus according to claim 1 , further comprising: a search condition designation area for displaying the search conditions; and a result display area for displaying the object.

4. The display means includes: The information processing apparatus according to claim 3 , wherein a search condition specification area for displaying the search conditions and a result display area for displaying the object are displayed on the same screen.

5. The calculation means is The information processing apparatus according to claim 1 , wherein the score is calculated so that the score increases as a certainty factor managed in association with an attribute that is the same as or similar to the attribute specified as the search condition increases.

6. The calculation means is The information processing apparatus according to claim 1 , further comprising: a score that is calculated so as to increase as the degree of similarity between an attribute similar to the attribute designated as the search condition increases.

7. The image processing device further includes an image analysis unit that analyzes the image to identify attributes of people included in the image and certainty of the attributes, The calculation means is The information processing apparatus according to claim 1 , wherein an attribute of the identified person and a certainty of the attribute are used as the search condition.

8. The calculation means is changing a certainty value of the attribute specified as the search condition and recalculating the score, and if the ranking of the scores of the two or more objects before changing the certainty value of the attribute specified as the search condition changes due to the recalculation of the score, specifying the changed certainty value as a threshold value; The display means includes: The information processing apparatus according to claim 1 , further comprising: displaying the threshold together with a certainty factor of an attribute designated as the search condition.

9. A method for managing at least one object, an attribute into which the object is classified, and a confidence level indicating a probability that the object has the attribute, in association with each other; calculating a score indicating a degree of match of the object with respect to the search criteria using a certainty of the attribute specified as the search criteria and a certainty associated with an attribute identical or similar to the attribute specified as the search criteria and managed; The display method further comprises displaying the object based on the calculated score.

10. A method for managing at least one object, an attribute into which the object is classified, and a confidence level indicating a probability that the object has the attribute in association with each other, calculating a score indicating a degree of match of the object with respect to the search criteria using a certainty of the attribute specified as the search criteria and a certainty associated with an attribute identical or similar to the attribute specified as the search criteria and managed; A program that causes a computer to execute the following: displaying the object based on the calculated score.

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