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    Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

    TitleStereo Vision Tracking of Multiple Objects in Complex Indoor Environments
    Publication TypeJournal Article
    Año de publicación2010
    AutoresMarron, M, Garcia, JC, Sotelo, MA, Pizarro, D, Mazo, M, Cañas, JM, Losada-Gutiérrez, C, Marcos, A
    Idioma de publicaciónEnglish
    JournalSensors
    Volumen10
    Número4
    Páginas8865-8887
    Fecha de publicación09/2010
    EditorialMDPI - Open Access Publishing
    Rank in category11/58
    JCR CategoryINSTRUMENTS & INSTRUMENTATION
    Palabras clavemobile robots, Multi-Object Tracking, position estimation, stereo-vision
    JCR Impact Factor1.821
    ISSN1424-8220
    URLhttp://www.mdpi.com/1424-8220/10/10/8865/
    DOI10.3390/s101008865
    Abstract

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

    Resumen

    This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

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    sensors-def.pdf1.04 MB