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Lecture Notes in Computer Science
This work addresses the problem of fast, online segmentation of moving objects in video. We pose this as a discriminative online semi-supervised appearance learning task, where supervising labels are autonomously generated by a motion segmentation algorithm. The computational complexity of the approach is significantly reduced by performing learning and classification on oversegmented image regions (superpixels), rather than per pixel. In addition, we further exploit the sparse trajectoriesdoi:10.1007/978-3-642-37444-9_5 fatcat:aycqmtnpnnhtlfhwnd3wzsgvea