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Group action recognition in soccer videos is a challenging problem due to the difficulties of group action representation and camera motion estimation. This paper presents a novel approach for recognizing group action with a moving camera. In our approach, ego-motion is estimated by the Kanade-Lucas-Tomasi feature sets on successive frames. The optical flow is then computed on compensated frames....
This paper presents a new method for detecting and merging redundant points in registered range data. Given a global representation from sequences of 3D points, the points are projected onto a virtual image plane computed from the intrinsic parameters of the sensor. Candidates for redundancy are collected per pixel which then are clustered locally via region growing and replaced by the clusterpsilas...
The multiple view geometry in space-time can represent multiple view geometry in the case where non-rigid arbitrary motions are viewed from multiple translational cameras. However, it requires many corresponding points and is sensitive to the image noise. In this paper, we investigate mutual projections of cameras in four-dimensional space, and show it enables us to reduce the number of corresponding...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and to be matched may be very large, or even redundantly represent the shape information present. Since selective attention is a basic mechanism of the visual system, we explore whether there is a subset of salient points that...
A problem of detecting changes in a region viewed by multiple overlapping cameras is addressed. We are exploring a background change detection method of multilayered orthoimages using spatiotemporal texture blocks. Each camera view is projected to create a spatially aligned multilayered background orthoimages. The multilayered orthoimages are subdivided into non-overlapping blocks, and each block...
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