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    Title: 多視角影像中的退化問題與參數估測
    Degeneracies and Parameter Estimation in Multiple View Images
    Authors: 詹凱軒
    Chan, Kai Hsuan
    Contributors: 何瑁鎧
    郭正佩
    唐政元
    Hor, Maw Kae
    Kuo, Pei Jeng
    Tang, Cheng Yuan
    詹凱軒
    Chan, Kai Hsuan
    Keywords: 退化
    參數估測
    多視角幾何
    緊要配置
    粒子群最佳化
    貼片匹配法
    degeneracy
    parameter estimation
    multiple view geometry
    critical configuration
    particle swarm optimization
    patch-based matching
    Date: 2013
    Issue Date: 2013-11-01 11:43:28 (UTC+8)
    Abstract: 多視角影像比起單一影像，可提供更多資訊，有助於影像之分析、比對與建模。相關研究諸如利用多視角影像進行三維模型重建、影像拼接、影像修補、利用多視角攝影機進行物體與人物追蹤、與四維動態模型捕捉等。然而，多視角影像的研究中，自動且精確的偵測影像對應點一直是個困難的問題。其中多視角影像的退化(degeneracy)問題，經常被研究者所忽略，而此一問題往往造成幾何關係上錯誤的估算，影響後續處理的精確度。
    本研究中我們所定義之退化問題涵蓋範圍較廣，包含傳統數學上的退化，以及同時考慮多視角幾何與影像紋路匹配所造成之問題，我們將這些問題歸納成三種類型並進行探討：第一種類型，當相機參數未知、且影像幾何關係也未估算時，需透過對應點進行影像幾何的計算，若這些對應點相對之三維座標與相機中心之配置，剛好落在特定曲面或平面之情況，則會造成錯誤的估算；第二種類型，當相機參數已知、或已估算求得影像幾何關係時，透過這些估算的幾何關係，進行對應點的轉換，在特定情況下也會造成錯誤的結果；第三種類型，當我們透過多視角幾何關係，結合影像紋路，利用貼片(patch-based)方法進行對應點相似度評估時，容易因為視角的差異、比例的差異、及貼片平面與物體表面的差異，造成無法正確評估之問題。
    我們針對這三種類型的退化問題，分別進行分析與探討，並提供適當的建議與處理方法，以避開可能遇到的退化狀況。同時，無論是在對應點的估算、多視角三維重建、與多視角幾何的評估等，通常需要透過強健的參數估測方法來求得，我們也分析、討論近年許多代表性的參數估測方法，並提出更穩健的估測方法，應用於處理特定退化問題。
    透過我們提出的退化規避方法，能有效的提高多視角影像處理與重建三維模型的精確度。
    Multiple view images carry much more information than that in single view images. This information is helpful in analyzing, matching, and reconstruction the points and models in real scenes. There are many related researches such as three-dimensional model reconstruction from multi-view images, multi-view image stitching, multi-view image inpainting, multi-view object and human tracking as well as four-dimensional dynamic model capture, etc. However, automatic and accurate corresponding point matching is one of the difficult problems in multiple view researches. Moreover, the multi-view degeneracy problems are normally ignored by researchers. These problems will include geometric estimation error and cause inaccuracy in subsequently processing.
    In this dissertation, the definition of the degeneracy covers a wider scope. It includes the traditional degeneracy as discussed in mathematics as well as the corresponding point matching error caused by the model inaccuracy in geometries and in textures. We classify these problems into three categories and provide methods and guidelines for avoiding the degeneracy problems in multi-view image processing. The first category assumes the camera parameters or the geometries (for example, the fundamental matrix) are unknown and which must be estimated using the corresponding points. If the 3D locations of the corresponding points and the camera centers fall into particular configurations, such as the ruled quadric, the camera parameters estimation may yield multiple solutions or erroneous results. The second category assumes the camera geometry is known or known geometries (for example, the fundamental matrix or the trifocal tensor) are used to transfer the corresponding points. It may cause erroneous estimation under certain conditions. The third category occurs if we use the patch-based method to estimate the similarity of the corresponding points in multiple views, it will cause unreasonable estimation due to different viewing angle, image scaling, or inconsistencies between the patch plane and the object surface.
    We propose various guidelines as well as processing methods in order to avoid the degeneracies. In addition, it generally requires robust parameter estimation methods to accomplish for the corresponding point estimations, the 3D reconstructions from multiple views, as well as for the multi-view geometries estimations. We analyzed the most representative parameter estimation methods developed in recent years and proposed the more robust methods that can be used to handle the specific degeneracy problems.
    Using the proposed methods and guidelines for degeneracy avoidance, we can effectively improve the accuracy of the multi-view image processing as well as 3D model reconstructions.
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    Description: 博士
    國立政治大學
    資訊科學學系
    96753501
    102
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0096753501
    Data Type: thesis
    Appears in Collections:[Department of Computer Science ] Theses

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