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ICIP
2007
IEEE
14 years 10 months ago
Multi-Modal Particle Filtering Tracking using Appearance, Motion and Audio Likelihoods
We propose a multi-modal object tracking algorithm that combines appearance, motion and audio information in a particle filter. The proposed tracker fuses at the likelihood level ...
Matteo Bregonzio, Murtaza Taj, Andrea Cavallaro
ICPR
2008
IEEE
14 years 10 months ago
Preceding car tracking using belief functions and a particle filter
This article presents a preceding car rear view tracking algorithm which utilizes a particle filter and belief function data fusion. Most of tracking applications resort to only o...
Christèle Lecomte, John Klein, Pierre Mich&...
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
14 years 2 months ago
Interactive evolutionary multi-objective optimization and decision-making using reference direction method
In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMO procedure to develop an algorit...
Kalyanmoy Deb, Abhishek Kumar
TEC
1998
106views more  TEC 1998»
13 years 8 months ago
Combining mutation operators in evolutionary programming
Abstract— Traditional investigations with evolutionary programming (EP) for continuous parameter optimization problems have used a single mutation operator with a parameterized p...
Kumar Chellapilla
TON
2002
175views more  TON 2002»
13 years 8 months ago
Compressed bloom filters
A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, f...
Michael Mitzenmacher