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» Learning Models for Object Recognition
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169
Voted
MM
2003
ACM
239views Multimedia» more  MM 2003»
15 years 8 months ago
Foreground object detection from videos containing complex background
This paper proposes a novel method for detection and segmentation of foreground objects from a video which contains both stationary and moving background objects and undergoes bot...
Liyuan Li, Weimin Huang, Irene Y. H. Gu, Qi Tian
110
Voted
MVA
2007
15 years 4 months ago
Semi-supervised Incremental Learning of Manipulative Tasks
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
Zhe Li, Sven Wachsmuth, Jannik Fritsch, Gerhard Sa...
128
Voted
PR
2007
102views more  PR 2007»
15 years 3 months ago
A robust incremental learning framework for accurate skin region segmentation in color images
In this paper, we propose a robust incremental learning framework for accurate skin region segmentation in real-life images. The proposed framework is able to automatically learn ...
Bin Li, Xiangyang Xue, Jianping Fan
ECCV
2008
Springer
16 years 5 months ago
Online Tracking and Reacquisition Using Co-trained Generative and Discriminative Trackers
Visual tracking is a challenging problem, as an object may change its appearance due to viewpoint variations, illumination changes, and occlusion. Also, an object may leave the fie...
Gérard G. Medioni, Qian Yu, Thang Ba Dinh
155
Voted
CVPR
2012
IEEE
13 years 5 months ago
Steerable part models
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
Hamed Pirsiavash, Deva Ramanan