A new method for the optical flow estimation and segmentation of moving objects 'NMES'

被引：0

作者：

Ourchani A. ^{[1
]}

Baarir Z.-E. ^{[1
]}

Taleb-Ahmed A. ^{[2
]}

机构：

[1] Department of Electrical Engineering, AISEL, University of Mohamed Khider, B.P 145 RP, Biskra

[2] Laboratory of Industrial and Human Automation, Mechanics and Computer Sciences, University of Valenciennes, Valenciennes Cedex 9

来源：

International Journal of Intelligent Systems Technologies and Applications | 2018年 / 17卷 / 1-2期

关键词：

Block-matching; Chan-Vese model; Colour feature; Frame difference; K-means; Moving object; Occlusion; Optical flow; Segmentation; Texture feature;

D O I：

10.1504/IJISTA.2018.091600

中图分类号：

学科分类号：

摘要：

Segmentation of moving objects in video sequence is essential task in computer vision. This paper focuses on developing a new method for discriminate moving objects from a static background, focusing on the combination of motion, colour and texture features. First, we have used blockmatching for computing the optical flow, we also have taken in consideration the result of frame difference, to improve the quality of the optical flow. Moreover, we have used the k-means clustering algorithm owing to group the pixels, having similar features. Second, the result of the grouping pixels is used as an input in Chan-Vese model, in order to attract the evolving contour of moving objects contours. To evaluate the performance of our proposed method, we experiment it on challenging sequences. It has shown that our method provides an improved segmentation results. © 2018 Inderscience Enterprises Ltd.

引用

页码：195 / 209

页数：14

共 43 条

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