Abstract: This ball game video analysis device: receives movie frames captured by cameras; computes the trajectory of the three-dimensional positions of a ball using the received multiple movie frames; determines, on the basis of a change in the ball trajectory, whether or not any action has been made by a player with respect to the ball; in the case when there has been such an action, selects, as an action frame, the movie frame corresponding to the timing at which said action was made; and identifies, from the action frame, a player who made that action.

Abstract: This ball game video analysis device: receives movie frames captured by cameras; computes the trajectory of the three-dimensional positions of a ball using the received multiple movie frames; determines, on the basis of a change in the ball trajectory, whether or not any action has been made by a player with respect to the ball; in the case when there has been such an action, selects, as an action frame, the movie frame corresponding to the timing at which said action was made; and identifies, from the action frame, a player who made that action.

Abstract: A person's behavior monitoring device includes a processor for acquiring a captured image of each of a plurality of cameras, acquiring information relating to a person requiring special attention by analyzing the captured image, and generating a monitoring image including the information, in which the processor determines, for each of the cameras, whether or not a person detected from the captured image is a long-time stayer who stays for a long-time in a capturing area of one of the cameras based on a result of tracking the person, and superimposes and displays a person rectangle that enables identification of a degree of stay on the captured image in correspondence with a person corresponding to the long-time stayer.

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: A person's behavior monitoring device includes a processor for acquiring a captured image of each of a plurality of cameras, acquiring information relating to a person requiring special attention by analyzing the captured image, and generating a monitoring image including the information, in which the processor determines, for each of the cameras, whether or not a person detected from the captured image is a long-time stayer who stays for a long-time in a capturing area of one of the cameras based on a result of tracking the person, and superimposes and displays a person rectangle that enables identification of a degree of stay on the captured image in correspondence with a person corresponding to the long-time stayer.

Abstract: The present disclosure provides a person tracking method of tracking a person with high precision. According to a person tracking method and a person tracking device of the present disclosure, a processor determines coordinates of a plurality of persons of a video within the video. The processor specifies a group area as an area where the persons of the video are dense. The processor tracks coordinates of a certain person within the video. The processor determines a locus of coordinates of the certain person in the group area based on coordinates of the certain person out of the group area and a number depicted on a clothing.

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: The present disclosure provides a person tracking method of tracking a person with high precision. According to a person tracking method and a person tracking device of the present disclosure, a processor determines coordinates of a plurality of persons of a video within the video. The processor specifies a group area as an area where the persons of the video are dense. The processor tracks coordinates of a certain person within the video. The processor determines a locus of coordinates of the certain person in the group area based on coordinates of the certain person out of the group area and a number depicted on a clothing.

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: 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: 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.

Abstract: The present invention is a posture estimation device for estimating a wide variety of 3-dimensional postures by using a skeletal model. The posture estimation device (200) has: a skeletal backbone estimation unit (230) for estimating the position of a feature location of a person within an acquired image; a location extraction unit (240) which generates a likelihood map indicating the certainty that a location other than the feature location of the person exists in the acquired image based on the position of the feature location of the person; and a skeletal model evaluation unit (250) for evaluating, based on the likelihood map, a candidate group which includes a plurality of 2-dimensional skeletal models as candidates and such that each 2-dimensional skeletal model is configured from a line group representing each location and a point group representing coupling between each location and corresponds to one posture of the person.

Abstract: Disclosed is an orientation state estimation device capable of estimating with high accuracy the orientation state of a jointed body. An orientation state estimation device (100) estimates the orientation state of a body on the basis of image data of the body having multiple parts connected by joints. The device is provided with: a likelihood map generation unit (150) which, from the image data, for at least two parts of the jointed body, generates a likelihood map showing the plausibility distribution of where each part is most plausibly positioned; and an orientation state estimation unit (160) which, when a learning likelihood map, which is associated in advance with an orientation state, and an estimated likelihood map, which is generated on the basis of the image data, coincide to a high degree, estimates that the orientation state associated with said learning likelihood map is the orientation state of 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: Disclosed is an object detection method capable of detecting with high precision information relating to a jointed object from image data. An object detection device (160) detects information relating to an object from image data of images captured of an object having multiple parts connected by joints. The disclosed object detection device (160) is provided with a joint angle extraction unit (161) which extracts the angle of a joint connecting two parts from candidates of the positions of two neighboring parts obtained from the image data, and a part length ratio estimation unit (165) which uses the joint angle to perform the detection described above.

Abstract: With this device, an edge pair likelihood map generation unit (120) computes an 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.