Abstract: A learning apparatus includes a first learning unit, a learning data generator, and a second learning unit. The first learning unit implements a learning process for a first classifier such that a class applicable degree of a candidate class corresponding to a correct answer class becomes the maximum as compared with class applicable degrees of other candidate classes. The learning data generator performs a classification process for a classification target using the first classifier already subjected to the learning process, converts class applicable degrees of a plurality of candidate classes, which are output by the first classifier already subjected to the learning process into a dimensionally compressed value based on a predetermined compression rule, and generates second learning data in which the identification target is associated with the dimensionally compressed value. The second learning unit implements a learning process for a second classifier using the second learning data.

Abstract: This posture state estimation device is capable of estimating with high accuracy the posture state of an object. The posture state estimation device (100) is a device for estimating the posture state of an object having a plurality of sections connected by joints on the basis of image data that images the object, and has a section candidate extraction unit (140) for extracting a section candidate for a section from the image data, a complementary section candidate extraction unit (160) which estimates that a portion of an unextracted section for which a section candidate has not been extracted is being shadowed by an already extracted section for which a section candidate has been extracted in order to extract a section candidate of the unextracted section, and a posture state estimation unit (170) for estimating the posture state of the object on the basis of the extracted section candidate.

Abstract: The present invention provides an electronic wallet having a higher level of anonymity, security and convenience, which is capable of efficient electronizing of value information as well as which allows the user to efficiently manage the electronic value information. A presentation card indicating the fixed property of an electronic value is digitally signed by the service provider; a variable property is digitally signed with the private key of that electronic value. A service control, security information, representation control and representation resource are digitally signed by the service provider. These digital signature will be authenticated each time an electronic value object is generated.

Abstract: A learning apparatus includes a first learning unit, a learning data generator, and a second learning unit. The first learning unit implements a learning process for a first classifier such that a class applicable degree of a candidate class corresponding to a correct answer class becomes the maximum as compared with class applicable degrees of other candidate classes. The learning data generator performs a classification process for a classification target using the first classifier already subjected to the learning process, converts class applicable degrees of a plurality of candidate classes, which are output by the first classifier already subjected to the learning process into a dimensionally compressed value based on a predetermined compression rule, and generates second learning data in which the identification target is associated with the dimensionally compressed value. The second learning unit implements a learning process for a second classifier using the second learning data.

Abstract: A processor of an orientation estimation device, as an orientation estimation method for estimating an orientation of a player existing in a sport video, receives reference orientation information which is information obtained based on information input by a user and which is information designating a joint position of a specific player existing in the sport video of an estimation target game and estimates an orientation of an estimation target player who is a player other than the specific player existing in a sport video of an estimation target using the reference orientation information.

Abstract: A learning device includes an input section and a learning section. The input section obtains training data in which an image containing an image of equipment of a vehicle, first information indicating a skeleton location of a specific part of a vehicle-occupant, and second information indicating a state of the vehicle-occupant with respect to the equipment are associated with each other. The learning section forms a model such that an estimating device can obtain the first information and the second information associated with the image containing the image of the equipment.

Abstract: An estimation device includes a storage section, an estimator, a likelihood calculator, and an output section. The storage section stores a model formed through machine learning. The estimator estimates a skeleton location of a specific part of a vehicle-occupant and a positional relation between equipment and the specific part, from image data containing an image of the equipment in a vehicle interior with the aid of the model stored in the storage section. The output section outputs the skeleton location information.

Abstract: This technology is a video processing method and a video processing device, in which a processor performs processing on video data of video obtained by capturing a sports game. A processor receives video data, calculates a motion amount of a player for each frame, from the received video data, and estimates at least one of a start frame of a play in the game, and an end frame at which an immediately preceding play, that is a one-previous play of the play, is ended, based on the calculated motion amount.

Abstract: A play segment extraction method or a play segment extraction device extracts a play segment of sports recorded in a sports video using a processor. The processor identifies a referee in a sports video, estimates a posture of the identified referee, estimates an operation of the referee from the estimated posture, and extracts a play segment, based on the estimated operation of the referee. Thereby, it is possible to accurately extract the play segment.

Abstract: A processor of an orientation estimation device, as an orientation estimation method for estimating an orientation of a player existing in a sport video, receives reference orientation information which is information obtained based on information input by a user and which is information designating a joint position of a specific player existing in the sport video of an estimation target game and estimates an orientation of an estimation target player who is a player other than the specific player existing in a sport video of an estimation target using the reference orientation information.

Abstract: This posture state estimation device is capable of estimating with high accuracy the posture state of an object. The posture state estimation device (100) is a device for estimating the posture state of an object having a plurality of sections connected by joints on the basis of image data that images the object, and has a section candidate extraction unit (140) for extracting a section candidate for a section from the image data, a complementary section candidate extraction unit (160) which estimates that a portion of an unextracted section for which a section candidate has not been extracted is being shadowed by an already extracted section for which a section candidate has been extracted in order to extract a section candidate of the unextracted section, and a posture state estimation unit (170) for estimating the posture state of the object on the basis of the extracted section candidate.

Abstract: This technology is a video processing method and a video processing device, in which a processor performs processing on video data of video obtained by capturing a sports game. A processor receives video data, calculates a motion amount of a player for each frame, from the received video data, and estimates at least one of a start frame of a play in the game, and an end frame at which an immediately preceding play, that is a one-previous play of the play, is ended, based on the calculated motion amount.

Abstract: An orientation estimation device includes a processor. The processor receives the analysis target image and sets a plurality of reference positions including a head position and a waist position of a person with respect to an input analysis target image. A candidate region of a part region in an analysis target image is determined based on a joint base link model in which an orientation of a person is defined by an arrangement of a plurality of point positions including the head position and the waist position and a plurality of the part regions and the plurality of set reference positions. It is determined whether the person included in the analysis target image takes the orientation or not based on a part image feature which is an image feature of a part region in an image obtained by photographing a person and an image feature of the determined candidate region.

Abstract: This posture state estimation device is capable of estimating with high accuracy the posture state of an object. The posture state estimation device (100) is a device for estimating the posture state of an object having a plurality of sections connected by joints on the basis of image data that images the object, and has a section candidate extraction unit (140) for extracting a section candidate for a section from the image data, a complementary section candidate extraction unit (160) which estimates that a portion of an unextracted section for which a section candidate has not been extracted is being shadowed by an already extracted section for which a section candidate has been extracted in order to extract a section candidate of the unextracted section, and a posture state estimation unit (170) for estimating the posture state of the object on the basis of the extracted section candidate.

Abstract: With this device, an edge pair likelihood map generation unit (120) computes edge pair likelihood which denotes the plausibility that a pixel of a pair is an edge of an estimation subject site, and generates an edge pair likelihood map which denotes the edge pair likelihood for each pixel. A continuity likelihood map generation unit (130) evaluates, upon the edge pair likelihood map, the continuity for the edge pair likelihood of a pixel which is included in a region wherein the estimate subject site is presumed, and generates a continuity likelihood map which denotes an edge pair likelihood which has continuity as a candidate region of the estimate subject site. An integrated likelihood map generation unit (140) generates an integrated likelihood map which denotes the candidate region which the continuity likelihood map denotes, refined based on a predetermined condition.

Abstract: A candidate region extraction unit (110) extracts candidate regions from an image by using a common characteristic amount. A part region extraction unit (120) separates a part region, which has a high likelihood of being a part, from a second-part candidate region other than the part region. A characteristic amount calculation unit (130) calculates the intrinsic characteristic amount of each of the part region and the second-part candidate region. A characteristic amount correction unit (140) corrects the intrinsic characteristic amount of either one of the candidate regions on the basis of the length, the width, and the angle of the other candidate region. A determination unit (150) determines whether or not the part region and the second-part candidate region are parts that constitute a pair on the basis of the similarity between the corrected intrinsic characteristic amount and the intrinsic characteristic amount of the other candidate region.

Abstract: The present invention provides an electronic wallet having a higher level of anonymity, security and convenience, which is capable of efficient electronizing of value information as well as which allows the user to efficiently manage the electronic value information. A presentation card indicating the fixed property of an electronic value is digitally signed by the service provider; a variable property is digitally signed with the private key of that electronic value. A service control, security information, representation control and representation resource are digitally signed by the service provider. These digital signature will be authenticated each time an electronic value object is generated.

Abstract: Provided is a posture estimation device with which it is possible to estimate the posture of an object having joints with a high degree of precision. A posture estimation device (100) carries out an estimation of a posture of an object on the basis of image data. An object having a plurality of sites which are connected by joints is photographed. The posture estimation device includes a reference model storage unit (140) which stores a reference model, which defines the locations of the sites, for each posture. A weighting computation unit (150) carries out weighting on the sites for each posture such that the weighting of concentrated parts is reduced. A posture estimation unit (160) estimates the posture of the object by applying the weighting and comparing the reference model with the object.

Abstract: A trajectory analyzing apparatus includes a matching unit that calculates the correlation between a forward trajectory obtained by tracking a moving object over pictures along the forward direction of the time axis and a backward trajectory obtained by tracking a moving object over the pictures along the backward direction of the time axis and a result output unit that outputs trajectory information indicating at least one of the forward trajectory, the backward trajectory, and an integrated trajectory obtained by integrating the forward trajectory and backward trajectory and indicating the degree of reliability of the at least one trajectory based on the calculated correlation.

Abstract: A posture estimation device, which is able to estimate the posture of a humanoid articulated body with high precision, has: a head estimation unit (120) that estimates the position of a person's head from image information for an image that contains a person; a foot estimation unit (130) that, from the image information, estimates the position of the person's foot for which the sole of the foot is parallel to the floor surface; and a posture estimation unit (140) that estimates the posture of the person on the basis of the relative positional relationship between the estimated head position and the estimated foot position. For example, the posture estimation unit (140) estimates the side on which the foot is located, with respect to the head, as the front side of the person.