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Tracking for planar objects is an important issue to vision-based robotic applications. In direct visual tracking (DVT) methods, the similarity between two images is often measured through the sum of squared differences (SSD) especially with the efficient second-order minimization (ESM) due to its simplicity and efficiency. However, SSD-based ESM is not robust to illumination changes since it is usually...
Recently, sparse representation-based tracking methods called l1 trackers give remarkable performances in difficult video sequences. However, the tracking in the situation of large illumination changes and shadow casting still has serious problems that need to be solved. A new illumination invariant tracking method based on photometric normalization techniques and sparse representation framework is...
In the field of nanotechnology, tracking freely swimming microorganisms under a microscope is difficult. An image of the target often rotates and changes shape as it moves. Further, the difficulty increases with background changes and fluctuations of colors and the brightness because of differences in the surrounding environment. To address these problems, we propose a tracking method combined with...
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