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CVPR
2010
IEEE
15 years 9 months ago
Unsupervised Learning of Invariant Features Using Video
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...
David Stavens, Sebastian Thrun
ICASSP
2007
IEEE
15 years 7 months ago
Breaking the Limitation of Manifold Analysis for Super-Resolution of Facial Images
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...
Sung Won Park, Marios Savvides
EVOW
2010
Springer
15 years 4 months ago
Towards Automated Learning of Object Detectors
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...
Marc Ebner
MTA
2010
162views more  MTA 2010»
14 years 8 months ago
Combining spatial and temporal patches for scalable video indexing
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...
ICIP
2009
IEEE
16 years 2 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
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...