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» Tracking with general regression
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AVSS
2006
IEEE
15 years 1 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
DICTA
2003
14 years 11 months ago
Probabilistic Multiple Cue Integration for Particle Filter Based Tracking
Robust visual tracking has become an important topic in the field of computer vision. The integration of cues such as color, edge strength and motion has proved to be a promising ...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...
PODS
2012
ACM
276views Database» more  PODS 2012»
13 years 12 days ago
Randomized algorithms for tracking distributed count, frequencies, and ranks
We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...
Zengfeng Huang, Ke Yi, Qin Zhang
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
15 years 7 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo
DAGSTUHL
2008
14 years 11 months ago
Interactive Multiobjective Optimization Using a Set of Additive Value Functions
Abstract. In this chapter, we present a new interactive procedure for multiobjective optimization, which is based on the use of a set of value functions as a preference model built...
José Rui Figueira, Salvatore Greco, Vincent...