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» Learning bilinear models for two-factor problems in vision
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ICIP
2005
IEEE
14 years 10 months ago
Visual tracking via efficient kernel discriminant subspace learning
Robustly tracking moving objects in video sequences is one of the key problems in computer vision. In this paper we introduce a computationally efficient nonlinear kernel learning...
Chunhua Shen, Anton van den Hengel, Michael J. Bro...
ICCV
2007
IEEE
14 years 11 months ago
Embedded Profile Hidden Markov Models for Shape Analysis
An ideal shape model should be both invariant to global transformations and robust to local distortions. In this paper we present a new shape modeling framework that achieves both...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
ECCV
2004
Springer
14 years 11 months ago
Extraction of Semantic Dynamic Content from Videos with Probabilistic Motion Models
Abstract. The exploitation of video data requires to extract information at a rather semantic level, and then, methods able to infer "concepts" from low-level video featu...
Gwenaëlle Piriou, Jian-Feng Yao, Patrick Bout...
ICPR
2000
IEEE
14 years 10 months ago
Growing Gaussian Mixture Models for Pose Invariant Face Recognition
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...
Ralph Gross, Jie Yang, Alex Waibel
ECCV
1998
Springer
14 years 11 months ago
Estimating Coloured 3D Face Models from Single Images: An Example Based Approach
In this paper we present a method to derive 3D shape and surface texture of a human face from a single image. The method draws on a general flexible 3D face model which is "le...
Thomas Vetter, Volker Blanz