Color Weighted Correspondence Algorithm for Stereo Vision
           

- 指導教授 黃漢邦 博士 研究生 張景富

- Advisor :Dr.Han-Pang Huang Student :Ching-Fu Chang

Lab. of Robotics., Department of Mechanical Engineering National Taiwan University Taiwan
Abstract:

In this paper, we propose a new method called “color weighted correspondence algorithm” to solve correspondence problems. Geometric constraints are added to reduce the ambiguities in stereo matching. Left-right consistency check is used to increase the confidence for matching results. Post-processing helps remove the outliers and make original dense disparity map smooth and reliable. The three-dimensional characteristics can be reconstructed by stereo triangulation.

Projected median is used to rectify cameras before performing the stereo matching in case mismatches happen. It performs well as the cameras are set up in approximately correct position. The YCC color model is adopted to simulate human vision system to deal with textureless regions. It is then applied to the “color weighted correspondence algorithm” to determine the correspondence. It validates the feasibility of humanoid color perception with stereo matching methodology to estimate depth and reconstruct 3D scene.

中文摘要:


本文的主要目的為發展適用於雙眼立體視覺系統的三維影像重建理論。我們提出一個新的方法來解決立體比對中最困難的對應點問題，並加入一些幾何的限制來減少 模零兩可的對應。經過雙向驗證的對應點比對更能確保在估測視差時的正確性。將稠密的視差圖經過後處理之後使其更為平滑可靠，再利用立體三角量測使之回復三 維景物的特徵。


當攝影機的擺設趨近於幾何限制，我們採用投射中值精確的校正以減少錯誤比對的發生。此外，藉由採用一色彩轉換模擬人類視覺系統，處 理立體比對中色彩資訊不豐富之區域，結果證實模擬人類視覺色彩認知結合所提出的比對方法能有效地偵測深度與重建三維場景。所提出的比對方法，除了能有效的 減少運算量以達到近即時之外，在影像深度不連續之區域的比對更有明顯的改善。