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CVPR
2008
IEEE
14 years 9 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
ICCV
2003
IEEE
14 years 9 months ago
Minimally-Supervised Classification using Multiple Observation Sets
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...
Chris Stauffer
PAMI
2008
231views more  PAMI 2008»
13 years 7 months ago
Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors
This paper describes methods for recovering time-varying shape and motion of nonrigid 3D objects from uncalibrated 2D point tracks. For example, given a video recording of a talkin...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
EMMCVPR
2009
Springer
14 years 2 months ago
Detection and Segmentation of Independently Moving Objects from Dense Scene Flow
We present an approach for identifying and segmenting independently moving objects from dense scene flow information, using a moving stereo camera system. The detection and segmen...
Andreas Wedel, Annemarie Meißner, Clemens Ra...
DICTA
2007
13 years 9 months ago
Visual Tracking Based on Color Kernel Densities of Spatial Awareness
We propose a kernel-density based scheme that incorporates the object colors with their spatial relevance to track the object in a video sequence. The object is modeled by the col...
Zhuan Qing Huang, Zhuhan Jiang