We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
A novel method for robust super-resolution offace images is proposed in this paper. Face super-resolution is a particular interest in video surveillance where face images have typ...
Recognizing arbitrary objects in images or video sequences is a difficult task for a computer vision system. We work towards automated learning of object detectors from video seque...
This paper tackles the problem of scalable video indexing. We propose a new framework combining spatial and motion patch descriptors. The spatial descriptors are based on a multisc...
Paolo Piro, Sandrine Anthoine, Eric Debreuve, Mich...
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...