Single object tracking based on active and passive detection information in distributed heterogeneous sensor network

Hyunhak Shin, Chuljin Cho, Hanseok Ko

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    In this paper, a single object tracking method based on fusion of detection information collected from a distributed heterogeneous sensor network is proposed. The considered sensor network is composed of one active type source and multiple receivers. It is assumed that the heterogeneous network is capable of acquiring both passive and active information simultaneously. By means of fusion of the acquired heterogeneous data, the proposed method estimates the candidate region of target location. Then, position of the object is estimated by Maximum Likelihood Estimation. In the experimental results, the performance of the proposed method is demonstrated in terms of deployment strategy of the heterogeneous sensor network.

    Original languageEnglish
    Title of host publication2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages444-449
    Number of pages6
    ISBN (Electronic)9781509038114
    DOIs
    Publication statusPublished - 2016 Nov 7
    Event13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016 - Colorado Springs, United States
    Duration: 2016 Aug 232016 Aug 26

    Publication series

    Name2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016

    Other

    Other13th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2016
    Country/TerritoryUnited States
    CityColorado Springs
    Period16/8/2316/8/26

    Bibliographical note

    Publisher Copyright:
    © 2016 IEEE.

    Copyright:
    Copyright 2017 Elsevier B.V., All rights reserved.

    ASJC Scopus subject areas

    • Signal Processing
    • Media Technology
    • Instrumentation
    • Computer Vision and Pattern Recognition

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