Robust regression methods for computer vision: a review
International Journal of Computer Vision
| Hi-index | 0.00 |
An active mesh representation of motion has been developed by the authors. It describes the motion in an image sequence by the trajectories of a set of nodes that form a mesh (also known as a control grid). In this paper we investigate how to cluster the nodes, or equivalently the mesh elements, so that the nodes in the same group have similar global motions. We present and compare two approaches. The parallel approach first finds a set of global motion parameters for each element and then partitions these parameters using the K-means clustering algorithm; The sequential (or layered) approach recursively extracts the nodes with the dominant motion from all the nodes, using a modified robust regression algorithm.