文化大學機構典藏 CCUR:Item 987654321/35897
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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/35897


    题名: Directional Prediction CamShift algorithm based on Adaptive Search Pattern for moving object tracking
    作者: Hsia, CH (Hsia, Chih-Hsien)
    Liou, YJ (Liou, Yun-Jung)
    Chiang, JS (Chiang, Jen-Shiun)
    贡献者: 電機系
    关键词: Moving object tracking
    DP-CamShift
    MeanShift
    Motion estimation
    Adaptive Search Pattern
    日期: 2016-06
    上传时间: 2017-04-13 14:37:31 (UTC+8)
    摘要: Moving object tracking is a fundamental task on smart video surveillance systems, because it provides a focus of attention for further investigation. Continuously Adaptive MeanShift (CamShift) algorithm is an adaptation of the MeanShift algorithm for moving objects tracking significantly, and it has been attracting increasing interests in recent years. In this work, a new CamShift approach, Directional Prediction CamShift (DP-CamShift) algorithm, is proposed to improve the tracking accuracy rate. According to the characteristic of the center-based motion vector distribution for the real-world video sequence, this work employs an Adaptive Search Pattern (ASP) to refine the central area search. The proposed approach is more robust because it adapts the optimal search pattern methods for the most adequate direction of the moving target. Since the fast Motion Estimation (ME) method has its own moving direction feature, we can adaptively use the most proper fast ME method to the certain moving object to have the best performance. Furthermore for estimation in large motion situations, the strategy of the DP-CamShift can preserve good performance. For the test video sequences with frame size of 320 x 240, the experimental results indicate that the proposed algorithm can have an accuracy rate of 99 % and achieve 23 frames per second (FPS) processing speed.
    關聯: JOURNAL OF REAL-TIME IMAGE PROCESSING 卷: 12期: 1 頁碼: 183-195
    显示于类别:[電機工程系] 期刊論文

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