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NIPS
2001
13 years 8 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
MMM
2005
Springer
202views Multimedia» more  MMM 2005»
14 years 1 months ago
Image Mining and Retrieval Using Hierarchical Support Vector Machines
For some time now, image retrieval approaches have been developed that use low-level features, such as colour histograms, edge distributions and texture measures. What has been la...
Ross Brown, Binh Pham
TSMC
2010
13 years 2 months ago
Toward Unconstrained Ear Recognition From Two-Dimensional Images
Abstract--Ear recognition, as a biometric, has several advantages. In particular, ears can be measured remotely and are also relatively static in size and structure for each indivi...
John D. Bustard, Mark S. Nixon
CVPR
2010
IEEE
14 years 1 months ago
Putting local features on a Manifold
Local features have proven very useful for recognition. Manifold learning has proven to be a very powerful tool in data analysis. However, manifold learning application for imag...
Marwan Torki and Ahmed Elgammal
ICMCS
2007
IEEE
208views Multimedia» more  ICMCS 2007»
13 years 11 months ago
A Cognitive and Unsupervised Map Adaptation Approach to the Recognition of the Focus of Attention from Head Pose
In this paper, the recognition of the visual focus of attention (VFOA) of meeting participants (as defined by their eye gaze direction) from their head pose is addressed. To this ...
Jean-Marc Odobez, Sileye O. Ba