基于曲线分组的多模态距离图像分割

M. Haindl, Pavel Zid
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引用次数: 4

摘要

介绍了一种针对一般人脸场景的快速距离图像分割方法。距离分割是基于对相互配准的距离和强度数据中存在于目标表面边界的阶跃不连续进行递归自适应概率检测。检测到的人脸轮廓引导随后的区域生长步骤,其中相邻的人脸曲线被组合在一起。基于曲线段的区域增长取代了传统方法中基于像素的区域增长,大大提高了算法的速度。对多模态数据的利用显著提高了分割质量
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimodal Range Image Segmentation by Curve Grouping
A fast range image segmentation method for scenes comprising general faced objects is introduced. The range segmentation is based on a recursive adaptive probabilistic detection of step discontinuities which are present at object face borders in mutually registered range and intensity data. Detected face outlines guides the subsequent region growing step where the neighbouring face curves are grouped together. Region growing based on curve segments instead of pixels like in the classical approaches considerably speed up the algorithm. The exploitation of multimodal data significantly improves the segmentation quality
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