近幾年所提出的立體匹配演算法中，學者們愈來愈追求精準度的情況下，往往運
算時間已經逐漸被忽略，導致實作出來的演算法無法應用在即時3D運算及播放系統
上，且現階段單張立體匹配演算法的研究也已逐漸遇到了瓶頸。故本論文的重點著重
在運算時間的即時性，以及方法創新這兩大重點下去論述。
本論文打破了在 [1]中所提出的立體匹配演算法四大架構，不使用需要大量運算
時間的匹配成本，也不須每點都計算視差值，取而代之的，而是先將具可信賴的邊界
點透過非精確性字串比對來找出對應的邊界點，再將視差值傳遞給尚未對應的點，並
利用鉛直投票以及濾波器精煉後處理來將深度圖的品質往上提升。
本論文所提出的方法均可利用GPU來平行處理以提升整體效能，對於運算時間的
即時性也有一定程度以上的貢獻。

In the recent proposed stereo matching algorithm, scholars have increasingly pursued accuracy. Computation time has gradually been ignored, which lead to the algorithm implemented cannot be applied to the real-time 3D computing and playback system. The research of stereo matching in single frame has been gradually encountered a bottleneck.
Therefore, this paper focuses on two key points: real-time computing as well as innovative methods.
This paper breaks the four stage stereo matching algorithm based on [1] as proposed, and does not need to calculate matching cost which requires lots of computation time.
Instead of calculating the disparity of each pixel, we use inexact string matching to find the corresponding edge pixel, and then propagate the disparity to the other unmatched pixel. In order to enhance the quality of the final result, we also use vertical voting and post processing filters to refine the depth map.
Each step of the algorithm is designed with parallelism considerations such that the computations can be accelerated with CUDA implementations on GPU.

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