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» Learning to Track with Multiple Observers
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TSP
2008
139views more  TSP 2008»
13 years 7 months ago
Bayesian Filtering With Random Finite Set Observations
This paper presents a novel and mathematically rigorous Bayes recursion for tracking a target that generates multiple measurements with state dependent sensor field of view and clu...
Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni
ICMCS
2007
IEEE
173views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Tracking Multiple Objects using Probability Hypothesis Density Filter and Color Measurements
Most methods for multiple object tracking in video represent the state of multi-objects in a high dimensional joint state space. This leads to high computational complexity. This ...
Nam Trung Pham, Weimin Huang, Sim Heng Ong
CVPR
1998
IEEE
14 years 9 months ago
Using Adaptive Tracking to Classify and Monitor Activities in a Site
We describe a vision system that monitors activity in a site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive tracker...
W. Eric L. Grimson, Chris Stauffer, R. Romano, L. ...
ISVC
2010
Springer
13 years 6 months ago
Exploiting Multiple Cameras for Environmental Pathlets
Abstract. We present a novel multi-camera framework to extract reliable pathlets [1] from tracking data. The proposed approach weights tracks based on their spatial and orientation...
Kevin Streib, James W. Davis
ICVS
2009
Springer
14 years 2 months ago
A Multiple Hypothesis Approach for a Ball Tracking System
This paper presents a computer vision system for tracking and predicting flying balls in 3-D from a stereo-camera. It pursues a “textbook-style” approach with a robust circle ...
Oliver Birbach, Udo Frese