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中文摘要：
为了将前景对象从多视点图像巾自动地分割出来，提出一种基于多视点图像特征分析的对象提取方法．首先采用改进的随机Hough变换提取极线平面图中的直线，并对已检测直线的斜率进行统计分析；然后根据对象在场景中所处的深度，将对应斜率的直线转换到原始图像空间中得到初始轮廓；并利用边缘生长方法缩短断开边缘的间距；最后采用边缘连接方法获得闭合的轮廓曲线．实验结果表明，与基于水平集的主动轮廓模型分割方法相比，文中方法能更加快速、精确地将对象从复杂场景巾分割出来．
英文摘要：
In order to segment foreground objects from multi view images automatically; an object extraction algorithm is proposed from multi-view images. Firstly, straight lines in epipolar plane image （EPI） are detected by an improved randomized Hough transform, and followed by a statistical analysis of the slopes of EPI lines. Then, according to the depth of the object under segmentation, the corresponding EPI lines are mapped back to the original image space to get an initial contour. After that, an edge growing method is used to reduce the gaps between broken edge segments. Finally, an edge linking method is adopted to obtain a closed contour curve. Experimental results show that, compared with the active contour segmentation methods based on level set, our method can extract objects from complicated scene more accurately and more efficiently.
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