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Object tracking is one of the most important components in numerous applications of computer vision. In this paper, the target is represented by a series of binary patterns, where each binary pattern consists of several rectangle pairs in variable size and location. As complementary to traditional binary descriptors, these patterns are extracted in both the intensity domain and the gradient domain...
Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks. This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels. On the contrary, our proposed method can obtain continuous depth...
Surface texture classification is an important aspect of computer vision and a well studied problem. In this paper, we greatly increase speed for texture classification while maintaining accuracy. We take inspiration form past work and propose a new method for texture classification which is extremely fast due to the low dimensionality of our feature space. We extract distinctive features at a very...
The task of recovering three-dimensional (3-D) geometry from two-dimensional views of a scene is called 3-D reconstruction. It is an extremely active research area in computer vision. There is a large body of 3-D reconstruction algorithms available in the literature. These algorithms are often designed to provide different tradeoffs between speed, accuracy, and practicality. In addition, even the...
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