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» Likelihood Map Fusion for Visual Object Tracking
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BMVC
2000
14 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
IJCV
2002
133views more  IJCV 2002»
14 years 9 months ago
Probabilistic Tracking with Exemplars in a Metric Space
Abstract. A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especia...
Kentaro Toyama, Andrew Blake
ICASSP
2010
IEEE
14 years 10 months ago
Visual localization and segmentation based on foreground/background modeling
In this paper, we propose a novel method to localize (or track) a foreground object and segment the foreground object from the surrounding background with occlusions for a moving ...
Hanzi Wang, Tat-Jun Chin, David Suter
ICPR
2006
IEEE
15 years 10 months ago
Object Tracking Using Globally Coordinated Nonlinear Manifolds
We present a dynamic inference algorithm in a globally parameterized nonlinear manifold and demonstrate it on the problem of visual tracking. An appearance manifold is usually non...
Che-Bin Liu, Ming-Hsuan Yang, Narendra Ahuja, Ruei...
ICMCS
2007
IEEE
138views Multimedia» more  ICMCS 2007»
15 years 4 months ago
Probabilistic Visual Tracking via Robust Template Matching and Incremental Subspace Update
In this paper, we present a probabilistic algorithm for visual tracking that incorporates robust template matching and incremental subspace update. There are two template matching...
Xue Mei, Shaohua Kevin Zhou, Fatih Porikli