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» An Adaptive Bayesian Technique for Tracking Multiple Objects
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ICCV
2007
IEEE
14 years 9 months ago
Graph Based Discriminative Learning for Robust and Efficient Object Tracking
Object tracking is viewed as a two-class 'one-versusrest' classification problem, in which the sample distribution of the target is approximately Gaussian while the back...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
ICIP
2003
IEEE
14 years 9 months ago
Mosaic of a video shot with multiple moving objects
In this paper we describe an application which takes a video shot as input and produces a compact representation composed by a background layer and segmented moving objects. We de...
Andrea Fusiello, M. Aprile, Roberto Marzotto, Vitt...
CVPR
2010
IEEE
14 years 27 days ago
Visual Tracking via Weakly Supervised Learning from Multiple Imperfect Oracles
Long-term persistent tracking in ever-changing environments is a challenging task, which often requires addressing difficult object appearance update problems. To solve them, most...
Bineng Zhong, Hongxun Yao, Sheng Chen, Xiaotong Yu...
CVPR
2012
IEEE
11 years 10 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
CHI
1995
ACM
13 years 11 months ago
Virtual Reality on a WIM: Interactive Worlds in Miniature
This paper explores a user interface technique which augments an immersive head tracked display with a hand-held miniature copy of the virtual environment. We call this interface ...
Richard Stoakley, Matthew Conway, Randy F. Pausch