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» Bacteria Filters: Persistent Particle Filters for Background...
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ICIP
2010
IEEE
13 years 7 months ago
Bacteria Filters: Persistent Particle Filters for Background Subtraction
Yair Movshovitz-Attias, Shmuel Peleg
IROS
2006
IEEE
145views Robotics» more  IROS 2006»
13 years 10 months ago
Panoramic Vision and Laser Range Finder Fusion for Multiple Person Tracking
– This paper describes a fusion of panoramic vision and laser range data to track multiple persons simultaneously from a stationary robot. Particle filters are used to track peop...
Punarjay Chakravarty, Ray Jarvis
CVPR
2004
IEEE
14 years 6 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...
ICCV
2001
IEEE
14 years 6 months ago
BraMBLe: A Bayesian Multiple-Blob Tracker
Blob trackers have become increasingly powerful in recent years largely due to the adoption of statistical appearance models which allow effective background subtraction and robus...
Michael Isard, John MacCormick
EMMCVPR
2011
Springer
12 years 4 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen