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» A Probabilistic Background Model for Tracking
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ICPR
2008
IEEE
15 years 6 months ago
Tracking human body by using particle filter Gaussian process Markov-switching model
The goal of this article is to present an effective and robust tracking algorithm for nonlinear feet motion by deploying particle filter integrated with Gaussian process latent v...
Jing Wang, Hong Man, Yafeng Yin
ICMCS
2005
IEEE
201views Multimedia» more  ICMCS 2005»
15 years 5 months ago
Head Tracking Using Particle Filter with Intensity Gradient and Color Histogram
This paper presents a method for tracking human head using a particle filter to naturally integrate two complementary cues: intensity gradient and color histogram. The shape of th...
Xinyu Xu, Baoxin Li
MICCAI
2009
Springer
16 years 29 days ago
Actin Filament Tracking Based on Particle Filters and Stretching Open Active Contour Models
We introduce a novel algorithm for actin filament tracking and elongation measurement. Particle Filters (PF) and Stretching Open Active Contours (SOAC) work cooperatively to simpli...
Hongsheng Li, Tian Shen, Dimitrios Vavylonis, X...
TREC
2007
15 years 29 days ago
Opinion Retrieval Experiments Using Generative Models: Experiments for the TREC 2007 Blog Track
Ranking blog posts that express opinions regarding a given topic should serve a critical function in helping users. We explored a couple of methods for opinion retrieval in the fr...
Yuki Arai, Koji Eguchi
ICIP
2002
IEEE
16 years 1 months ago
Likelihood-based object detection and object tracking using color histograms and EM
The topic of this paper is the integration of Expectation Maximization (EM) background modeling and template matching using color histograms as templates to improve person trackin...
Paul J. Withagen, Klamer Schutte, Frans C. A. Groe...