Motion feature descriptor based moving objects segmentation

A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descriptor （MFD） is designed to describe motion feature of each block in a picture based on...

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Bibliographic Details
Published in高技术通讯（英文版） Vol. 18; no. 1; pp. 84 - 89
Main Author Yuan Hui Chang Yilin Ma Yanzhuo Bai Donglin Lu Zhaoyang
Format Journal Article
LanguageEnglish
Published State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an 710071, P.R.China%Xian Communication Institute, Xi'an 710106, P.R.China 01.03.2012
Subjects
MFD
分割方法
模糊C-均值聚类算法
特征描述
运动信息
运动强度
运动物体分割
运动特征
motion feature descriptor (MFD)
video analysis
fuzzy C-means clustering
moving objects segmentation
motion estimation (ME)
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Summary:A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descriptor （MFD） is designed to describe motion feature of each block in a picture based on motion intensity, motion in occlusion areas, and motion correlation among neighbouring blocks. Then, a fuzzy C-means clustering algorithm （FCM） is implemented based on those MFDs so as to segment moving objects. Moreover, a new parameter named as gathering degree is used to distinguish foreground moving objects and background motion. Experimental results demonstrate the effectiveness of the proposed method.
Bibliography:motion estimation （ME）, motion feature descriptor （MFD）, fuzzy C-means clustering, .moving objects segmentation, video analysis
A novel moving objects segmentation method is proposed in this paper. A modified three dimensional recursive search （3DRS） algorithm is used in order to obtain motion information accurately. A motion feature descriptor （MFD） is designed to describe motion feature of each block in a picture based on motion intensity, motion in occlusion areas, and motion correlation among neighbouring blocks. Then, a fuzzy C-means clustering algorithm （FCM） is implemented based on those MFDs so as to segment moving objects. Moreover, a new parameter named as gathering degree is used to distinguish foreground moving objects and background motion. Experimental results demonstrate the effectiveness of the proposed method.
11-3683/N
ISSN:1006-6748
DOI:10.3772/j.issn.1006-6748.2012.01.014