Abstract: Systems, apparatuses, devices and methods for body pose tracking are provided that are simple, inexpensive, flexible, accurate and robust. One body pose tracking system includes a mobile device, such as a smartphone, and active or passive marker bands. Images and depth information captured by the smartphone may be analyzed using an Inverse Kinematic (IK) model, and, in certain cases, the IK model solution may be augmented by machine learning. Other body pose tracking systems include an augmented-reality/virtual-reality (AR/VR) head-mounted-display (HMD) and/or AR/VR glasses rather than a smartphone. An AR/VR HMD device may include a depth sensor and multiple environment-facing cameras.

Abstract: Systems, apparatuses, devices and methods for body pose tracking are provided that are simple, inexpensive, flexible, accurate and robust. One body pose tracking system includes a mobile device, such as a smartphone, and active or passive marker bands. Images and depth information captured by the smartphone may be analyzed using an Inverse Kinematic (IK) model, and, in certain cases, the IK model solution may be augmented by machine learning. Other body pose tracking systems include an augmented-reality/virtual-reality (AR/VR) head-mounted-display (HMD) and/or AR/VR glasses rather than a smartphone. An AR/VR HMD device may include a depth sensor and multiple environment-facing cameras.

Abstract: A computer-implemented method comprises obtaining first data comprising a first collection of coordinate data representing a position, or positions, of a first group of one or more objects detected in a first frame of a scene and obtaining second data comprising a second collection of coordinate data representing a position, or positions, of a second group of one or more objects detected in a second frame of the scene, wherein the second frame represents a different view of the scene than the first frame. The method further comprises determining whether any of the first group of objects correspond to any of the second group of objects in the scene based on the first collection of coordinate data and the second collection of coordinate data, wherein the first frame and the second frame are obtained from image data captured from a single camera position.

Abstract: A computer-implemented method comprises obtaining first data comprising a first collection of coordinate data representing a position, or positions, of a first group of one or more objects detected in a first frame of a scene and obtaining second data comprising a second collection of coordinate data representing a position, or positions, of a second group of one or more objects detected in a second frame of the scene, wherein the second frame represents a different view of the scene than the first frame. The method further comprises determining whether any of the first group of objects correspond to any of the second group of objects in the scene based on the first collection of coordinate data and the second collection of coordinate data, wherein the first frame and the second frame are obtained from image data captured from a single camera position.

Abstract: In an image sensor, high-speed recognition processing is performed using high-speed image data, which is different from low-speed image data used for displaying. In the image sensor, an imaging element captures an image of an object and generates frames of image data arranged in time series. A binarization processing unit performs binarization processing on each of the frames to generate binarized frames. A tracking processing unit generates a difference between binarized frames adjacent in time series and tracks a change in a position of the object included in the binarized frames.

Abstract: In an image sensor, high-speed recognition processing is performed using high-speed image data, which is different from low-speed image data used for displaying. In the image sensor, an imaging element captures an image of an object and generates frames of image data arranged in time series. A binarization processing unit performs binarization processing on each of the frames to generate binarized frames. A tracking processing unit generates a difference between binarized frames adjacent in time series and tracks a change in a position of the object included in the binarized frames.

Abstract: An arithmetic apparatus comprises a plurality of cascade-connected arithmetic units. Each of the plurality of arithmetic units comprises: a calculator configured to operate in one of a rotation mode of performing a rotation calculation, and a vectoring mode of calculating a rotation angle; and a holding unit configured to hold rotational direction information output from the calculator in the vectoring mode. In addition, when operating in the rotation mode, the calculator performs the rotation calculation on data input from an arithmetic unit in a preceding stage, based on the rotational direction information held in the holding unit.

Abstract: When deducing a homography matrix representing a geometrical relationship between two images, an image processing apparatus obtains a transformation matrix for four feature points in each of the two images based on reference coordinates. More specifically, the apparatus obtains the area of a triangle formed by three out of the four feature points, and calculates projective parameters of transformation matrices from the area ratios. The apparatus calculates the homography matrix between the images by the product of one of the two obtained matrices and an inverse matrix of the other.

Abstract: When deducing a homography matrix representing a geometrical relationship between two images, an image processing apparatus obtains a transformation matrix for four feature points in each of the two images based on reference coordinates. More specifically, the apparatus obtains the area of a triangle formed by three out of the four feature points, and calculates projective parameters of transformation matrices from the area ratios. The apparatus calculates the homography matrix between the images by the product of one of the two obtained matrices and an inverse matrix of the other.

Abstract: An arithmetic apparatus comprises a plurality of cascade-connected arithmetic units. Each of the plurality of arithmetic units comprises: a calculator configured to operate in one of a rotation mode of performing a rotation calculation, and a vectoring mode of calculating a rotation angle; and a holding unit configured to hold rotational direction information output from the calculator in the vectoring mode. In addition, when operating in the rotation mode, the calculator performs the rotation calculation on data input from an arithmetic unit in a preceding stage, based on the rotational direction information held in the holding unit.