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ICML
2005
IEEE
14 years 8 months ago
Q-learning of sequential attention for visual object recognition from informative local descriptors
This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
Lucas Paletta, Gerald Fritz, Christin Seifert
ACCV
2006
Springer
14 years 1 months ago
Boosted Algorithms for Visual Object Detection on Graphics Processing Units
Nowadays, the use of machine learning methods for visual object detection has become widespread. Those methods are robust. They require an important processing power and a high mem...
Hicham Ghorayeb, Bruno Steux, Claude Laurgeau
BDA
2000
13 years 9 months ago
Visual Exploration of Temporal Object Databases
Two complementary families of users' tasks may be identified during database visualization: data browsing and data analysis. On the one hand, data browsing involves extensive...
Chaouki Daassi, Marlon Dumas, Marie-Christine Fauv...

Publication
468views
13 years 4 months ago
Visual object tracking via sample-based Adaptive Sparse Representation (AdaSR)
When appearance variation of object and its background, partial occlusion or deterioration in object images occurs, most existing visual tracking methods tend to fail in tracking ...
Zhenjun Han, Jianbin Jiao, Baochang Zhang, Qixiang...
CVPR
2007
IEEE
14 years 9 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann