NDLI: Discriminative Descriptor-Based Observation Model for Visual Tracking

Content Provider	IEEE Xplore Digital Library
Author	Wen-Yan Chang Chu-Song Chen Yi-Ping Hung
Copyright Year	2006
Description	Author affiliation: Inst. of Inf. Sci., Acad. Sinica, Taipei (Wen-Yan Chang; Chu-Song Chen; Yi-Ping Hung)
Abstract	Varying illumination and partial occlusion are two main difficulties in visual tracking. Existing methods based on appearance information cannot solve these problems effectively since appearance is sensitive to lighting and the appearances under occlusions are quite different. In this paper, we propose a descriptor-based dynamic tracking approach that can track objects under partial occlusions and varying illumination. Instead of global appearance, an object is represented by a set of invariant feature descriptors that are generated from local regions around some salient points. By integrating the local descriptor information into the observation model, our method is effective under varying illumination and partial occlusions
Sponsorship	IEEE CPS
Starting Page	83
Ending Page	86
File Size	501060
Page Count	4
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.455
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lighting Filtering Particle tracking Histograms Monte Carlo methods Robustness Motion analysis Pattern recognition Bayesian methods Target tracking
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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