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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 資訊工程學系 > 會議論文  >  Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/14027


    Title: Background Modeling from GMM Likelihood Combined with Spatial and Color Coherency
    Authors: Sheng-Yan Yang
    Chiou-Ting Hsu
    Date: 2006
    Publisher: Institute of Electrical and Electronics Engineers Inc
    Keywords: Gaussian processes
    Markov processes
    filtering theory
    image colour analysis
    image representation
    image segmentation
    object detection
    video signal processing
    GMM likelihood
    Gaussian mixture model
    Markov random field
    adaptive thresholding scheme
    background model
    clustering process
    color coherency
    filtering step
    nonparametric method
    spatial coherency
    video frame segmentation
    Abstract: This paper proposes to combine spatial and color coherency with the pixel-wise GMM to determine the background model. We first represent each pixel with a hybrid feature vector, which includes its GMM likelihood, color and spatial features, and estimate the density for each video frame by a non-parametric method. Next, we apply a clustering process to segment the video frame into clusters with similar hybrid features. Finally, we replace the background likelihood for each cluster with the GMM likelihood in the cluster mode. Hence, the resulting background model becomes a smoothed GMM in terms of spatial and color coherency. For accurate object detection, we develop an adaptive thresholding scheme using Markov random field. Moreover, in order to reduce the computational load, we also propose a filtering step to skip pixels from the time-consuming clustering process. Our experimental results and comparisons demonstrate that the proposed background model indeed achieves better detection results with accurate object contours even in dynamic scenes
    Relation Link: http://webservices.ieee.org/pindex_basic.html
    URI: http://nthur.lib.nthu.edu.tw/handle/987654321/14027
    Appears in Collections:[資訊工程學系] 會議論文
    [資訊系統與應用研究所] 會議論文

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