摘要：
This paper provides a brief history review of the use of ancient weirs in fishing on our planet, as well as a pilot study that involves investigating and mapping the coastal heritage of ancient stone tidal weirs (STWs) in the Penghu Archipelago which is located in the Taiwan Strait. The spatial distribution and morphological features of STWs across Penghu Archipelago were investigated and analyzed using very high-resolution (VHR) and freely available Google Earth (GE) imagery and geographic information system (GIS) analysis tools. A total of 539 ground-truthed STWs were identified from multiple temporal GE images, and these accounted for over 90% of the localized inventory databases. The proposed GE-based method was found to be more efficient, timely and effective compared to field and airborne surveys. This paper illustrates the utility of GE as a source of freely available VHR remote sensing imagery for archaeological surveys and heritage sustainability in coastal areas.
作者机构：
[Zou, Changqing; Peng, Xiaojiang] Hengyang Normal Univ, Dept Phys & Elect Informat Sci, Hengyang, Peoples R China.;[Chen, Shifeng; Zou, Changqing; Lv, Hao] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen Key Lab CVPR, Shenzhen, Peoples R China.;[Zou, Changqing] Univ Chinese Acad Sci, Shenzhen Coll Adv Technol, Beijing, Peoples R China.;[Fu, Hongbo] City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China.;[Liu, Jianzhuang] Chinese Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China.
摘要：
3-D object modeling from single images has many applications in computer graphics and multimedia. Most previous 3-D modeling methods which directly recover 3-D geometry from single images require user interactions during the whole modeling process. In this paper, we propose a semi-automatic 3-D modeling approach to recover accurate 3-D geometry from a single image of a piecewise planar object with less user interaction. Our approach concentrates on these three aspects: (1) requiring rough sketch input only, (2) accurate modeling for a large class of objects, and (3) automatically recovering the invisible part of an object and providing a complete 3-D model. Experimental results on various objects show that the proposed approach provides a good solution to these three problems. (C) 2014 Elsevier Ltd. All rights reserved.
会议名称：
27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
会议时间：
JUN 23-28, 2014
会议地点：
Columbus, OH
会议主办单位：
[Zou, Changqing;Liu, Jianzhuang] Shenzhen Inst Adv Technol, Shenzhen Key Lab CVPR, Shenzhen, Peoples R China.^[Zou, Changqing] Hengyang Normal Univ, Dept Phys & Elect Informat Sci, Hengyang, Peoples R China.^[Zou, Changqing] Univ Chinese Acad Sci, Beijing, Peoples R China.^[Yang, Heng] Queen Mary Univ London, London, England.^[Liu, Jianzhuang] Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong, Hong Kong, Peoples R China.^[Liu, Jianzhuang] Huawei Technol Co Ltd, Media Lab, Shenzhen, Peoples R China.
会议论文集名称：
IEEE Conference on Computer Vision and Pattern Recognition
关键词：
3D reconstruction;Line drawing decomposition;Line drawing separation;Split face
摘要：
Reconstructing 3D objects from single line drawings is often desirable in computer vision and graphics applications. If the line drawing of a complex 3D object is decomposed into primitives of simple shape, the object can be easily reconstructed. We propose an effective method to conduct the line drawing separation and turn a complex line drawing into parametric 3D models. This is achieved by recursively separating the line drawing using two types of split faces. Our experiments show that the proposed separation method can generate more basic and simple line drawings, and its combination with the example-based reconstruction can robustly recover wider range of complex parametric 3D objects than previous methods.
