.png){kind=icon}
返回
Markov random field modeled range image segmentation
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2003.10.017.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper range image segmentation is cast in the framework of Bayes inference and Markov random field modeling. To facilitate the inference from distance measurement to labeling set, we introduce the set of surface function parameters as another estimation and construct a novel model accordingly. Subsequent study shows that range image segmentation can be formulated as a combinatorial optimization problem. This model-based optimization will be used as a postprocessing module after an edge-based initial segmentation in our hybrid segmentation scheme. Qualitative improvement is observed from experimental results. (C) 2003 Elsevier B.V. All rights reserved.
Keyword:
range image segmentation
Markov random fields
Bayesian inference
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.6W
机构
暂无机构信息
引用论文
.png){kind=icon}
Crystal chemistry and metal-hydrogen bonding in anisotropic and interstitial hydrides of intermetallics of rare earth (R) and transition metals (T), RT3 and R2T7稀土 (R) 和过渡金属 (T) 的金属间化合物的各向异性和间隙氢化物中的晶体化学和金属氢键，RT3 和R2T7
PREAI
分享收藏Large submarine landslides in the Japan Trench: A new scenario for additional tsunami generation
OAAI
OAAI分享收藏
查看更多内容