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Optimized particles for 3-D tracking

Huiying Chen, Youfu Li

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

    Abstract

    3-D visual tracking is useful for many of its applications. In this paper, we propose two different ways for different system configurations to optimize particle filter for enhancing 3-D tracking performances. On one hand, a new data fusion method is proposed to obtain the optimal importance density function for active vision systems. On the other hand, we develop a method for reconfigurable vision systems to maximize the effective sampling size in particle filter, which consequentially helps to solve the degeneracy problem and minimize the tracking error. © 2010 Springer-Verlag.
    Original languageEnglish
    Title of host publicationIntelligent Robotics and Applications
    Subtitle of host publicationThird International Conference, ICIRA 2010, Proceedings
    PublisherSpringer Verlag
    Pages749-761
    Volume6424 LNAI
    EditionPART 1
    ISBN (Print)3642165834, 9783642165832
    DOIs
    Publication statusPublished - 2010
    Event3rd International Conference on Intelligent Robotics and Applications, ICIRA 2010 - Shanghai, China
    Duration: 10 Nov 201012 Nov 2010

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume6424 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference3rd International Conference on Intelligent Robotics and Applications, ICIRA 2010
    PlaceChina
    CityShanghai
    Period10/11/1012/11/10

    Research Keywords

    • 3-D tracking
    • effective sampling size
    • importance density function
    • particle filter

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