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CVPR
2005
IEEE
16 years 1 months ago
Combining Object and Feature Dynamics in Probabilistic Tracking
Objects can exhibit different dynamics at different scales, and this is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image fea...
Leonid Taycher, John W. Fisher III, Trevor Darrell
CVPR
2010
IEEE
15 years 5 hour ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
ECCV
2004
Springer
16 years 1 months ago
Towards Intelligent Mission Profiles of Micro Air Vehicles: Multiscale Viterbi Classification
In this paper, we present a vision system for object recognition in aerial images, which enables broader mission profiles for Micro Air Vehicles (MAVs). The most important factors ...
Sinisa Todorovic, Michael C. Nechyba
ICPR
2008
IEEE
15 years 6 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock
CVPR
2006
IEEE
15 years 5 months ago
Satellite Features for the Classification of Visually Similar Classes
We show that the discrimination between visually similar classes often depends on the detection of socalled ‘satellite features’. These are local features which are not inform...
Boris Epshtein, Shimon Ullman