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» Boosting Object Detection Using Feature Selection
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ICIP
2005
IEEE
16 years 6 months ago
Object tracking based on morphological elastic graph matching
This paper presents a novel method for real-time tracking of objects in video sequences. Tracking is performed using the so-called Morphological Elastic Graph Matching algorithm. ...
Georgios N. Stamou, Nikos Nikolaidis, Ioannis Pita...
CVPR
2009
IEEE
15 years 2 months ago
Multi-object tracking through occlusions by local tracklets filtering and global tracklets association with detection responses
This paper presents an online detection-based two-stage multi-object tracking method in dense visual surveillances scenarios with a single camera. In the local stage, a particle f...
Junliang Xing, Haizhou Ai, Shihong Lao
FGR
2004
IEEE
205views Biometrics» more  FGR 2004»
15 years 8 months ago
Oriented Filters for Object Recognition: an Empirical Study
Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations....
Jerry Jun Yokono, Tomaso Poggio
ICIP
2010
IEEE
15 years 3 months ago
Sparse shapes prototype modeling using genetic algorithms
The process of finding representative shape patterns from sparse datasets is a challenging task: especially for non-rigid objects, shape deformations through time can produce very...
Stefano Maludrottu, Hany Sallam, Carlo S. Regazzon...
CVPR
2010
IEEE
16 years 28 days ago
Online Multiple Instance Learning with No Regret
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Li Mu, James Kwok, Lu Bao-liang