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» Learning to Track with Multiple Observers
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TSP
2008
139views more  TSP 2008»
14 years 9 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»
15 years 4 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
15 years 11 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
14 years 8 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
15 years 4 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