Face tracking in realistic environments is a difficult problem due to pose variations, occlusions of objects, illumination changes and cluttered background, among others. The paper...
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...
This paper addresses the problem of learning object models from egocentric video of household activities, using extremely weak supervision. For each activity sequence, we know onl...
This paper presents a new object-based segmentation technique which exploits a large temporal context in order to get coherent and robust segmentation results. The segmentation pr...
–Three-dimensional imaging applications require high resolution images that finally result in high data volumes. Due to bandwidth and storage restrictions, an efficient and robus...