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» Learning to Track Objects Through Unobserved Regions
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FGR
2000
IEEE
163views Biometrics» more  FGR 2000»
13 years 11 months ago
Tracking Interacting People
A computer vision system for tracking multiple people in relatively unconstrained environments is described. Trackerformed at three levels of abstraction: regions, people and grou...
Stephen J. McKenna, Sumer Jabri, Zoran Duric, Harr...
TOMCCAP
2010
202views more  TOMCCAP 2010»
13 years 2 months ago
Audio-visual atoms for generic video concept classification
We investigate the challenging issue of joint audio-visual analysis of generic videos targeting at semantic concept detection. We propose to extract a novel representation, the Sh...
Wei Jiang, Courtenay V. Cotton, Shih-Fu Chang, Dan...
EDUTAINMENT
2006
Springer
13 years 9 months ago
The ARTable: An AR-Based Tangible User Interface System
Augmented Reality (AR) and Tangible User Interface (TUI) have been proven to provide intuition to human computer interface with richness of a tactile sense. Recent implementations ...
Youngmin Park, Woontack Woo
CVPR
2007
IEEE
14 years 1 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
13 years 8 months ago
Maintaining diversity through adaptive selection, crossover and mutation
This paper presents an Adaptive Genetic Algorithm (AGA) where selection pressure, crossover and mutation probabilities are adapted according to population diversity statistics. Th...
Brian McGinley, Fearghal Morgan, Colm O'Riordan