影像序列于空間-時間域之切割問題研究

Abstract

在本論文當中, 提出了一套新的動態影像切割技術。目前動態影像切割的技術大多使用了運動向量估測技術(Motion estimation)來估測影像當中時間座標軸上的運動資訊。 然而這些技術通常會遭遇到孔徑問題(Aperture problem)、變形問題(Distortion problem)以及遮蔽問題(Occlusion problem)，而使得運動向量的預測產生錯誤。在這篇論文當中，為了避免上述問題的發生，我們設計了一套新的動態影像切割方法。將動態影像切割轉換到空間時間座標系(Spatio-temporal domain)當中處理，而動態影像切割問題將會轉換成一個三維空間中立體影像物件的切割問題。在我們的做法中，我們先將影像序列的色彩資訊轉換到CIE L* a* b*色彩空間中，藉以得到貼近人類視覺系統知覺的色彩關係。然後利用平面上四個不同方向的方向性天秤運算子(Directional Balance Operator)來找出影像中色彩資訊的趨勢變化，再根據這些趨勢將影像當中色彩資訊對比值較小的區域合併，進而得到二維的影像切割。而三維空間中立體影像的切割，則經由二維影像切割的技術，對三維空間中三個互相垂直的平面組施以二維影像切割。然後將三組二維影像切割的結果結合，最後再經過後處理(Post-processing)的過程，得到三維立體物件的切割。經過實驗結果顯示，影像序列中大面積的物體可以得到相當正確的切割。

In this thesis, we propose a novel approach of motion segmentation. Conventional motion segmentation approaches usually utilize motion estimation to acquire the temporal information of the image sequence. However, this approach basically cannot handle the aperture problem, distortion problem, and occlusion problem. In this thesis, we propose a different approach to avoid these problems. We translate the transform of an image sequence into the spatio-temporal domain. With this translation, the motion segmentation issue becomes a 3-D object segmentation issue in the spatio-temporal domain. In our approach, we first transform the image sequence from RGB color space to CIE L* a* b* color space to achieve the color presentation similar to the perception of human visual system. Then, we perform four directional Balance operators on the image to search for the change points of the color trend. According to these change points, the low contrast regions are merged and then the 2-D image segmentation is achieved. About 3-D object segmentation, we apply the proposed 2-D segmentation approach to three perpendicular planes in the spatio-temporal domain. After combining these 2-D segmentation results together and applying some post-processing, the 3-D object segmentation is completed. The simulation result indicates that the objects in the image sequence can be segmented correctly.