近幾年來, 很多的立體匹配演算法被提出用於生成更為精準的深度資訊, 但大部分的演算法都只考慮單一時間的資訊. 在這種情況下, 因為參考的資訊有限會造成精準度的瓶頸, 此外, 在一整串序列當中因為物件的移動和鄰近資訊的變化而造成閃爍的影響.
為了解決以上的問題, 我們提出一種演算法在考慮時間和空間上的資訊後使得深度圖更為精準和在序列上更為平順. 這篇論文主要分為兩個部分: 首先,我們先根據左右圖找出對應的深度圖, 再找出時間序列上每一張圖的對應點把時間上的資訊納入考量. 其後使用左右檢測,雙向濾波去除深度圖的雜訊. 最後利用時間上的中值濾波器使得序列更為平順.

In the recent year, many methods is developed for stereo matching to generate a better depth map, but lots of them consider an instant time only. It will meet a bottleneck to the accuracy because of the limited information. Moreover, the depth map of a video sequence will flicker due to the movement of the object and the neighborhood of each pixel.
In order to solve the problem mention above, in this thesis an algorithm which considers the spatial-temporal information is proposed to enhance the accuracy and the consistency in a sequence. The paper is divided into three parts. The first part is to compute the disparity between the left and the right images according to the similarity. Then, we search the corresponding pixel between the before and after frame and add the temporal cost into consideration. Third, we perform post processing such as left-right check and bilateral filter to de-noise. Temporal median smooth the flickering and discontinuity as a sequence.

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