Directional prediction CamShift algorithm based on adaptive search pattern for moving object tracking
學年 104
學期 2
出版（發表）日期 2016-06-01
作品名稱 Directional prediction CamShift algorithm based on adaptive search pattern for moving object tracking
作品名稱（其他語言）
著者 Hsia, Chih-Hsien; Liou, Yun-Jung; Chiang, Jen-Shiun
單位 淡江大學電機工程學系 中國文化大學電機工程學系研究所
出版者 Heidelberg: Springer
著錄名稱、卷期、頁數 Journal of Real-Time Image Processing 12(1), pp.183-195
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 × 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.
關鍵字 Moving object tracking;DP-CamShift;MeanShift;Motion estimation;Adaptive Search Pattern
語言 en
ISSN 1861-8200;1861-8219
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Jen-Shiun Chiang
審稿制度 否
國別 DEU
公開徵稿
出版型式 ,電子版,紙本
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