|Place of Conferral||北京|
|Keyword||重复结构检测 对称性检测 建筑立面图像标注 建筑立面图像解析|
|Other Abstract||Facade repetition detection is an important task in facade image understanding. This task can facilitate many computer vision problems, including building modeling and 3D reconstruction, facade image analysis, urban scene understanding and so on. However, this problem has the following three difficulties. First, for repetitive structures on facades of different architectural styles, there is usually significant discrepancy among their appearances and layouts. This limits the generality of repetition detection approaches. Second, among the repetitions on a single facade, there are usually appearance variations caused by blind slides, shutter rotations and so on. Third, facade images are often degraded due to corruptions including occlusions, glass reflections and changing illuminations. Because of the above two difficulties, it becomes difficult to measure the similarities between the repetitions. To deal with the above difficulties, the property that facade repetitions are horizontally and vertically aligned requires to be utilized. For this purpose, this thesis proposes two models describing the alignment property, namely a matrix multiplication based model and fiducial lines passing along repetition boundaries. Combining with the shape, color and other features of the facade repetitions, this thesis proposes several effective approaches for repetition detection. Specifically, the main contributions of this thesis contain the following four aspects.|
1. An explicit matrix factorization based approach is proposed. This approach utilizes a matrix multiplication based model to describe the alignment property among the facade repetitions. That is, the repetitions are viewed as the product of a repetitive pattern and two block matrices. The two block matrices are composed of alternating zero matrices and identity matrices, and record the vertical and horizontal positions of the repetitions respectively. Based on the model, repetition detection turns into a matrix factorization problem which optimizes the block matrices. An optimization algorithm is thus developed to solve the matrix factorization problem, where dynamic programming is used to optimize the block matrices. Extensive experiments demonstrate the effectiveness of the approach.
2. By localization, extraction and symmetry based optimization, an approach is proposed. This approach is characterised by detecting repetitions without requiring any labeled data. The approach contains three main modules. First, rectangle detection is conducted as facade structures are usually rectangular. Second, from the detected rectangles, the rectangles corresponding to real facade structures are extracted. Third, based on the extracted rectangular structures, an optimization problem is formulated to find all the repetitive structures. To solve the optimization problem, an efficient dynamic programming based algorithm is also developed. Comprehensive experimental results demonstrate the validity and effectiveness of the proposed approach.
3. An approach based on fiducial lines extraction is proposed. Since repetitions are horizontally and vertically aligned, they can be localized by the horizontal and vertical lines passing along the repetition boundaries. Based on the observation, the approach proposes to detect repetitions by extracting these fiducial lines. First, candidate lines are detected, containing both all the fiducial lines and many mistaken lines passing across facade wall or repetitive structures. Then, to pick out the fiducial lines, a maximum a posterior problem is formulated to measure the probabilities that the lines can localize the repetitions. Finally, the problem is efficiently solved by a dynamic programming based algorithm. Extensive qualitative and quantitative results verify the effectiveness of the approach.
4. An approach based on distribution distance maximization is proposed. Since the repetitions are generally rectangular, and horizontally and vertically aligned, this approach proposes to use fiducial lines, namely the horizontal and vertical lines passing along the repetition boundaries, to constrain the repetition segmentation. The problem of facade repetition segmentation is finally formulated as a constrained optimization problem, in which the segmentation determined by the fiducial lines is optimized by maximizing the distance between the foreground/background color distributions. An efficient dynamic programming based algorithm is also developed to solve the optimization problem. Experimental results on two publicly available datasets demonstrate the feasibility and validity of the proposed approach.
|肖鸿飞. 建筑立面图像重复结构检测方法研究[D]. 北京. 中国科学院研究生院,2017.|
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