We present a novel framework for motion segmentation that combines the concepts of layer-based methods and feature-based motion estimation. We estimate the initial correspondences...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. This observation is of...
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...