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» Probabilistic Object Tracking Using Multiple Features
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CLEAR
2007
Springer
195views Biometrics» more  CLEAR 2007»
14 years 1 months ago
Multi-level Particle Filter Fusion of Features and Cues for Audio-Visual Person Tracking
In this paper, two multimodal systems for the tracking of multiple users in smart environments are presented. The first is a multiview particle filter tracker using foreground, c...
Keni Bernardin, Tobias Gehrig, Rainer Stiefelhagen
ICIP
2004
IEEE
14 years 9 months ago
A probabilistic framework for object recognition in video
We propose a solution to the problem of object recognition given a continuous video sequence containing multiple views of an object. Initially, object models are acquired from ima...
Omar Javed, Mubarak Shah, Dorin Comaniciu
ACCV
2007
Springer
14 years 1 months ago
Probability Hypothesis Density Approach for Multi-camera Multi-object Tracking
Object tracking with multiple cameras is more efficient than tracking with one camera. In this paper, we propose a multiple-camera multiple-object tracking system that can track 3D...
Nam Trung Pham, Weimin Huang, S. H. Ong
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 7 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong
ACCV
2007
Springer
14 years 1 months ago
Spatiotemporal Oriented Energy Features for Visual Tracking
This paper presents a novel feature set for visual tracking that is derived from “oriented energies”. More specifically, energy measures are used to capture a target’s multi...
Kevin Cannons, Richard Wildes