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» Incremental Learning for Visual Tracking
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ICPR
2008
IEEE
14 years 4 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

Publication
313views
13 years 10 months ago
Visual Surveillance: Dynamic Behavior Analysis at Multiple Levels
New cameras are installed daily all around the world. Hence it becomes increasingly important to develop methods for reducing the manual effort that is still required for video ana...
Michael D. Breitenstein
BMVC
2000
13 years 11 months ago
Quantifying Ambiguities in Inferring Vector-Based 3D Models
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Eng-Jon Ong, Shaogang Gong
SASO
2007
IEEE
14 years 4 months ago
Emergence of Smooth Pursuit using Chaos
The task of tracking an object has been fully studied and many solutions presented before. However, it is a perfect test bed for the study of a novel model using Coupled Chaos Sys...
Boris Duran, Giorgio Metta, Giulio Sandini
ICPR
2008
IEEE
14 years 4 months ago
Relevant pattern selection for subspace learning
In this paper, we propose a scheme to improve the performance of subspace learning by using a pattern(data) selection method as preprocessing. Generally, a training set for subspa...
Jin Hee Na, Seok Min Yun, Minsoo Kim, Jin Young Ch...