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	NeUDF: Learning Neural Unsigned Distance Fields With Volume Rendering 期刊论文 OAI收割 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2024, 卷号: 46, 期号: 4, 页码: 2364-2377 作者: Liu, Yu-Tao; Wang, Li; Yang, Jie; Chen, Weikai; Meng, Xiaoxu \| 收藏 \| 浏览/下载：15/0 \| 提交时间：2024/05/20 Surface reconstruction Rendering (computer graphics) Image reconstruction Shape Image color analysis Topology Surface texture Unsigned distance fields volume rendering shape reconstruction from multi-view images open surfaces
	Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割 6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X. 收藏 \| 浏览/下载：33/0 \| 提交时间：2013/03/25 This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.
	Partial occlusion detection of object boundary (EI CONFERENCE) 会议论文 OAI收割 2009 IEEE Intrumentation and Measurement Technology Conference, I2MTC 2009, May 5, 2009 - May 7, 2009, Singapore, Singapore 作者: Zhang J.; Zhang K.; Zhang K.; Zhang K.; Zhang K. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 Partial occlusion is a difficult problem in computer vision since whether the object is changed or occluded is ambiguous especially when distinguishing it only from the object boundary. In this paper we proposed a novel idea to solve this problem by taking shape matching as a morphing processing. A mass-spring model is constructed from the point set which is sampled from a template (or reference) object boundary by moving it to a target object which is deformed and/or occluded. From the morphing processing sufficient information can be obtained and an accurate detection of occlusion is performed. By using of the proposed method the application scope of occlusion detection is expanded while other method cannot be performed which need color texture or motion information. The experiments performed on synthetic and real world images proved the satisfactory performance of the proposed method. 2009 IEEE.
	基于贝叶斯网络的纹理图像模型学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2008 作者: 王强收藏 \| 浏览/下载：52/0 \| 提交时间：2015/09/02 贝叶斯网络纹理模型纹理合成纹理分类从纹理恢复形状尺度不变特征 Bayesian network texture model texture synthesis texture classification shape from texture scale-invariant feature