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» Probabilistic Object Tracking Using Multiple Features
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CLEAR
2007
Springer
195views Biometrics» more  CLEAR 2007»
15 years 11 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
16 years 6 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
15 years 11 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»
15 years 4 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
15 years 11 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