| 摘要: |
| 提出了一种基于表面法向的高斯混合模型的距离图像分割算法.它充分利用了表面法向高斯混合模型的物理含义,使数据聚类的次数减少,并利用Expectation-Maximization(EM)算法估计出的模型参数计算模型的后验概率实现了自动模型选择.算法针对两种距离相机的60幅真实距离图像进行了实验.将实验结果与几个流行的分割算法进行了客观比较. |
| 关键词: 距离图像分割 高斯混合模型 EM算法 贝叶斯因子 |
| DOI： |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60275008 (国家自然科学基金) |
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| A Range Image Segmentation Algorithm Based on Gaussian Mixture Model |
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XIANG Ri-Hua,WANG Run-Sheng
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| Abstract: |
| A range image segmentation algorithm based on Gaussian mixture model of surface normal is proposed. It decreases the times of clustering computing by fully utilizing the physical meaning of Gaussian mixture model of surface normal, and achieves automatic model selection via the posterior probabilities computed from the model parameter estimated by Expectation-Maximization (EM) algorithm. Experimental results on 60 real range images from two kinds of range cameras are compared objectively with some popular segmentation algorithms. |
| Key words: range image segmentation Gaussian mixture model EM algorithm Bayes factor |
