CASIA OpenIR  > 毕业生  > 博士学位论文
基于图像的建筑结构场景的三维重建研究
其他题名A Study on Architectural Scene Reconstruction from Images
王伟
学位类型工学博士
导师胡占义
2014-11-29
学位授予单位中国科学院大学
学位授予地点中国科学院自动化研究所
学位专业模式识别与智能系统
关键词建筑场景重建 深度图 能量最小化 匹配扩散 用户交互 Architectural Scene Reconstruction Depth Map Energy Minimization Match Propagation User Interaction
摘要基于图像的室外场景重建是计算机视觉研究的重要方向之一,在文化遗产保护、数字化城市建模、虚拟现实等领域有着广泛的应用。然而,由于光照变化、透视畸变、弱纹理区域等诸多因素的影响,传统重建方法通常难以可靠地恢复完整的场景结构。为了克服以上困难,本文针对室外城市建筑场景重建中的完整性与效率等问题进行了系统的探讨与研究,取得的主要成果有: 1. 提出一种利用像素级及区域级匹配扩散的方式获取完整深度图的算法。其中,像素级匹配扩散用于快速获取纹理丰富区域的深度信息,并以此构造可靠的约束条件,进而使得能量优化框架下的区域级匹配扩散可以有效地解决弱纹理、倾斜表面等区域的重建问题。 2. 提出一种适于建筑场景重建的基于能量优化的空间平面拟合算法。此算法通过空间点的快速扩散与平面先验融合,在能量优化框架下可以快速从初始稀疏空间点中抽取更多、更可靠的空间平面以表达场景结构,有效克服了传统多模型拟合算法在场景重建时易于遗漏真实的空间平面和效率不高的缺点。 3. 提出一种基于多级能量优化的多视图分段平面重建算法。算法在能量优化框架下通过融合场景结构先验与几何约束,并采用多级能量优化的方式获取完整、准确的场景结构,不但有效地解决了弱纹理、倾斜表面等区域的重建问题,而且克服了传统相关算法过于依赖图像过分割的精度、难以恢复场景结构的细节等缺点。 4. 提出一种利用用户交互的方式快速对场景进行重建的算法。通过用户采用2D交互的方式快速指定重建区域及输入相关结构先验,算法可以有效地恢复场景中的平面及曲面(如球面、柱面等)结构,克服了传统相关算法过于依赖场景分段平面假设的缺点,进而可以获得更准确的重建结果。
其他摘要Architectural scene reconstruction from multiple images is one of hotly pursued topics in computer vision community in recent years, and finds its application in a variety of fields such as architecture heritage preservation, digital city-scale modeling, and virtual reality. However, due to various adverse factors,such as illumination variation, perspective distortion, poorly textured regions,most existing stereo methods usually could only recover some incomplete scene structure. In addition, the computational efficiency is also a major concern when the high resolution images are used.This thesis focuses primarily on the reconstruction completeness and computational efficiency, two key issues in architectural scene reconstruction. The main results include: 1. We proposed an effective method to obtain complete depth maps through pixel-level and region-level match propagations. The pixel-level match propagation can rapidly obtain accurate depths for those regions with abundant textures and provide effective constraints for the subsequent region-level match propagation, which is a follow-up of the former one to infer depths for poorly textured regions and highly slanted surfaces. The two propagations are both formulated and worked out under the energy minimization framework, which provides ample flexibility to tackle the problems in a unified manner. 2. We proposed a new energy-based plane-fitting method for architectural scene reconstruction from multiple images. Based on reconstructed initial sparse spatial points, the method can effectively and efficiently extract more reliable spatial planes to explain the scene structures through two steps: generating reliable candidate planes using spatial point match propagation and globally optimizing spatial planes by incorporating plane priors. Our proposed method is shown able to adequately overcome the two drawbacks of the traditional multi-model fitting methods, incomplete reconstruction and low computational efficiency under high resolution images. 3. We proposed an effective multi-view piecewise planar stereo method based on multi-level energy optimization. By incorporating the prior knowledge of scenes and geometric constraints in terms of carefully designed energy potentials,the method can not only recover complete depths for low textured regions or slanted surface, it can also handle the inevitable inaccuracy problem of initially segmented superpixels, a severe headache for the traditional piecewise plan...
其他标识符201118014628060
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6659
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
王伟. 基于图像的建筑结构场景的三维重建研究[D]. 中国科学院自动化研究所. 中国科学院大学,2014.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
CASIA_20111801462806(2231KB) 暂不开放CC BY-NC-SA请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[王伟]的文章
百度学术
百度学术中相似的文章
[王伟]的文章
必应学术
必应学术中相似的文章
[王伟]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。