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SENSYS
2003
ACM
15 years 5 months ago
Tracking a moving object with a binary sensor network
In this paper we examine the role of very simple and noisy sensors for the tracking problem. We propose a binary sensor model, where each sensor’s value is converted reliably to...
Javed A. Aslam, Zack J. Butler, Florin Constantin,...
CVPR
2004
IEEE
16 years 1 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
AMDO
2006
Springer
15 years 3 months ago
Monocular Tracking with a Mixture of View-Dependent Learned Models
This paper considers the problem of monocular human body tracking using learned models. We propose to learn the joint probability distribution of appearance and body pose using a m...
Tobias Jaeggli, Esther Koller-Meier, Luc J. Van Go...
IJCV
2008
188views more  IJCV 2008»
14 years 12 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
ICASSP
2011
IEEE
14 years 3 months ago
Video object tracking with differential Structural SIMilarity index
The Structural SIMilarity Measure (SSIM) combined with the sequential Monte Carlo approach has been shown [1] to achieve more reliable video object tracking performance, compared ...
Artur Loza, Fanglin Wang, Jie Yang, Lyudmila Mihay...