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 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 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: 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 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: A human detection and tracking apparatus prevents errors in a size of a person and a location of body parts between actual image data and a tracking result. Human frame detecting section detects, from first image data, a human frame as a region having high possibility of presence of a human, based on human feature data representing a feature of an entire human body. Body part frame location determining section determines a body part frame in the first image data, based on part feature data illustrating a feature of a body part of the human and a part frame determined as a region having high possibility of presence of a body part of the human in second image data previous to the first image data. Body part frame location correcting section corrects, based on the human frame, a location of the part frame determined in the first image data.

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: 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: Provided is a person detection device with which it is possible to estimate a state of a part of a person from an image. A person detection device (100) comprises: an evaluation unit (430) which acquires a prescribed outline of a person from an evaluation image; and a shoulder position calculation unit (440) and an orientation estimation unit (500) which estimate a state of a prescribed part of a person which is included in the evaluation image from the prescribed outline of the person which is acquired from the evaluation image, on the basis of an estimation model which denotes a relation between the prescribed outline and the state of the prescribed part of the person.

Abstract: A human detection and tracking apparatus prevents errors in a size of a person and a location of body parts between actual image data and a tracking result. Human frame detecting section detects, from first image data, a human frame as a region having high possibility of presence of a human, based on human feature data representing a feature of an entire human body. Body part frame location determining section determines a body part frame in the first image data, based on part feature data illustrating a feature of a body part of the human and a part frame determined as a region having high possibility of presence of a body part of the human in second image data previous to the first image data. Body part frame location correcting section corrects, based on the human frame, a location of the part frame determined in the first image data.

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 wherein an object having a plurality of sites which are connected by joints is photographed. The device comprises: 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) which carries out weighting on the sites for each posture such that the weighting of concentrated parts is reduced; and a posture estimation unit (160) which estimates the posture of the object by applying the weighting and comparing the reference model with the object.

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: 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: 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: Provided is a person detection device with which it is possible to estimate a state of a part of a person from an image. A person detection device (100) comprises: an evaluation unit (430) which acquires a prescribed outline of a person from an evaluation image; and a shoulder position calculation unit (440) and an orientation estimation unit (500) which estimate a state of a prescribed part of a person which is included in the evaluation image from the prescribed outline of the person which is acquired from the evaluation image, on the basis of an estimation model which denotes a relation between the prescribed outline and the state of the prescribed part of the person.

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: 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: A virtual machine with a stack architecture includes: a stack 120 whose top level (TOS) and the second level from the top (SOS) are mapped to registers of a real machine 201; an instruction storing unit 102 for storing a virtual machine instruction sequence to be executed; next instruction information storing unit 101 for storing a plurality of sets of next instruction information that are each associated with a different virtual machine instruction in the virtual machine instruction sequence, the set of next instruction information for a given virtual machine instruction indicating a change in a number of sets of data stored in the stack 120 due to execution of a virtual machine instruction executed after the given virtual machine instruction; a decoding unit 103 for decoding a virtual machine instruction and an associated set of next instruction information after reading them from the instruction storing unit 102 and the next instruction information storing unit 101; and an executing unit 110 for executing

Abstract: A Just-In-Time compiler is provided for use with a virtual machine that executes a virtual machine instruction sequence under the control of a real machine. The compiler converts parts of the virtual machine instruction sequence into the real machine instruction sequence before execution and includes a block start information unit that determines whether the encoded block start information indicates a corresponding virtual machine instruction would correspond to the start of a basic block if the virtual machine instruction sequence was divided into basic blocks. A converting unit converts the virtual machine instructions into real machine instruction sequences and an outputting unit rearranges the real machine instruction sequences from the converting unit into basic blocks in accordance with the block start information. Additionally, the compiler can be enabled by a program stored on a computer readable recording medium.