Combining region-based differential and matching algorithms to obtain accurate motion vectors for moving object in a video sequence

Chieh-Ling Huang, Yuh-Ren Choo, P. Chung
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引用次数: 1

Abstract

Motion estimation plays an important role in image processing, since temporal information has been regarded as a promising feature for both image segmentation and video coding. In this paper a hybrid approach is proposed to integrate a differential (gradient-based) optical flow approach and region-based matching approach to search for accurate object motion vectors. Our method adopts the Horn-Schunck optical flow constraint, in conjunction with several proposed techniques to convert the dense optical flow field to region-based motion field, and thereby suppress noise. The region-based matching approach is a modified version of the traditional block-matching algorithm, so that it can operate in region-based mode, and thereby enhance the visual effectiveness near the edges. Therefore, the proposed hybrid method has the tendency to obtain the estimation of "true" object motion inherited by the gradient-based approach, and also the superior visual effectiveness inherited by the block-matching approach.
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结合基于区域的差分和匹配算法,获得视频序列中运动物体的精确运动向量
运动估计在图像处理中起着重要的作用,因为时间信息被认为是图像分割和视频编码的一个有前途的特征。本文提出了一种结合微分(基于梯度)光流法和基于区域的匹配法的混合方法来搜索精确的目标运动向量。我们的方法采用Horn-Schunck光流约束,结合几种提出的技术将密集光流场转换为基于区域的运动场,从而抑制噪声。基于区域的匹配方法是对传统块匹配算法的改进,使其能够以基于区域的方式进行操作,从而增强了边缘附近的视觉效果。因此,所提出的混合方法既能继承基于梯度的方法对“真实”目标运动的估计,又能继承块匹配方法优越的视觉效果。
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