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» Modeling Moving Objects over Multiple Granularities
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IWCM
2004
Springer
14 years 26 days ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...
ICCV
2001
IEEE
14 years 9 months ago
Learning Image Statistics for Bayesian Tracking
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
Hedvig Sidenbladh, Michael J. Black
INFOCOM
2003
IEEE
14 years 23 days ago
Opportunistic Fair Scheduling over Multiple Wireless Channels
Abstract— Emerging spread spectrum high-speed data networks utilize multiple channels via orthogonal codes or frequency-hopping patterns such that multiple users can transmit con...
Yonghe Liu, Edward W. Knightly
ICCV
1995
IEEE
13 years 11 months ago
Recovering 3D Motion of Multiple Objects Using Adaptive Hough Transform
—We present a method to determine 3D motion and structure of multiple objects from two perspective views, using adaptive Hough transform. In our method, segmentation is determine...
Tina Yu Tian, Mubarak Shah
CEC
2008
IEEE
14 years 2 months ago
Path optimization for multiple objectives in directed graphs using genetic algorithms
Abstract— This paper presents a genetic algorithmic approach for finding efficient paths in directed graphs when optimizing multiple objectives. Its aim is to provide solutions...
Juan Rada, Ruben Parma, Wilmer Pereira