• Title/Summary/Keyword: centroid low-rate-frame

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Fuzzy Quantization and Rate Control for Very Low Bit­rate Video Coder (초저전송율 동영상 부호기를 위한 퍼지 양자화 및 율 제어에 관한 연구)

  • 양근호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.8
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    • pp.1684-1690
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    • 2003
  • In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

Object Tracking Algorithm Using Weighted Color Centroids Shifting (가중 컬러 중심 이동을 이용한 물체 추적 알고리즘)

  • Choi, Eun-Cheol;Lee, Suk-Ho;Kang, Moon-Gi
    • Journal of Broadcast Engineering
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    • v.15 no.2
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    • pp.236-247
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    • 2010
  • Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.