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» Self-Organizing, Adaptive Data Fusion for 3d Object Tracking
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ARCS
2005
Springer
9 years 11 months ago
Self-Organizing, Adaptive Data Fusion for 3d Object Tracking
Data fusion concepts are a necessary basis for utilizing complex networks of sensors. A key feature for a robust data fusion system is adaptivity, both to be fault-tolerant and to...
Olaf Kähler, Joachim Denzler
CVPR
2003
IEEE
9 years 11 months ago
Appearance Management and Cue Fusion for 3D Model-Based Tracking
This paper presents a systematic approach to acquiring model appearance information online for monocular modelbased tracking. The acquired information is used to drive a set of co...
Nils Krahnstoever, Rajeev Sharma
BMVC
2000
9 years 7 months ago
Quantifying Ambiguities in Inferring Vector-Based 3D Models
This paper presents a framework for directly addressing issues arising from self-occlusions and ambiguities due to the lack of depth information in vector-based representations. V...
Eng-Jon Ong, Shaogang Gong
ICPR
2006
IEEE
10 years 6 months ago
Detection-Assisted Initialization, Adaptation and Fusion of Body Region Trackers for Robust Multiperson Tracking
In this paper, we present a system for simultaneous tracking of multiple persons in a smartroom using multiple cameras. Robust person tracks are created, continuously adapted, and...
Keni Bernardin, Alexander Elbs, Rainer Stiefelhage...
ICPR
2002
IEEE
10 years 6 months ago
A Bayesian Approach to Video Object Segmentation via Merging 3D Watershed Volumes
In this paper, we propose a Bayesian approach to video object segmentation. Our method consists of two stages. In the first stage, we partition the video data into a set of 3D wate...
Yi-Ping Hung, Yu-Pao Tsai, Chih-Chuan Lai
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