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» Tracking Complex Objects Using Graphical Object Models
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ICIP
2003
IEEE
14 years 10 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
IJCV
2008
241views more  IJCV 2008»
13 years 9 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 8 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
BMVC
2010
13 years 7 months ago
Active 3D Segmentation through Fixation of Previously Unseen Objects
We present an approach for active segmentation based on integration of several cues. It serves as a framework for generation of object hypotheses of previously unseen objects in n...
Mårten Björkman, Danica Kragic
SPIEVIP
2010
13 years 11 months ago
Automatic scene activity modeling for improving object classification
In video surveillance, automatic methods for scene understanding and activity modeling can exploit the high redundancy of object trajectories observed over a long period of time. ...
Samuel Foucher, Marc Lalonde, Langis Gagnon