以深度圖像修補為基礎之3D建模

近年來，深度攝影機的價格越趨近便宜，令更多的研究者能夠使用深度攝影機。相對原本的二維影像，增加深度資訊對於電腦視覺的應用有很大的幫助，但是目前從深度攝影機得到原始的深度影像都有破洞、邊緣不完整、雜訊等問題。因此本論文提出了一個深度影像的修補方法，並將修補後的影像以3D重建的方式重現。首先，對破洞的部分進行偵測，並使用破洞周圍有效的深度資訊以及背景的深度資訊進行破洞的修補。再來，在複雜背景下，彩色資訊的邊緣不明顯，我們使用形態學和中值濾波器對邊緣做修正。在簡單背景下，使用彩色圖像的邊緣對深度圖像進行校正。最後，將得到無破洞且邊緣較完整的深度影像以Kinect Fusion的方法重建3D模型。

關鍵字

Kinect Fusion ；深度資訊； 3D模型

並列摘要

In recent years, the price of depth camera became low, so that researchers can use depth camera to do more application. For computer vision, depth images can provide more useful information. However, generally there are some problems in depth image, such as holes, incomplete edge, and temporal random fluctuations. Therefore, this paper proposes a depth image inpainting method applying on 3D object reconstruction. First, in the holes filling part we use No-measured pixels detection to locate the position of no-measured pixels, and then use the pixels which is near to nmd-pixels to estimate the depth information. Secondly, in complex background the edge of the color image is not obvious, so that we use erosion and dilation operation and median filter to smooth the edge. In simple background, we use our edge modified method to correct the edge of depth image depend on color image. Finally, we use 3D reconstruction method, Kinect Fusion, proposed by Microsoft to modeling the object.

並列關鍵字

Kinect Fusion ； Depth image ； 3D reconstruction ； temporal random fluctuations

參考文獻

[6] 賴韋名，盲人避障輔助系統之設計，淡江大學電機工程學系碩士論文，民國一百零二年。

[2] C. Cheng, S. Lin, S. Lai, and J. Yang,” Improved Novel View Synthesis from Depth Image with Large Baseline,” in Proc. of the International Conference on Pattern Recognition (ICPR) , 2008, pp.1-4.

[3] M. Camplani and L. Salgado, “Efficient spatio-temporal hole filling strategy for Kinect depth maps, ”Proceedings of SPIE, Vol. 8290, 2012.

[4] F. Qi, J. Han, P. Wang, G. Shi, and Fu Li, “Structure guided fusion for depth map inpainting,”Pattern Recognition Letters, Vol. 34, 2013, pp.70-76.

[5] M. Schmeing and X. Jiang, “Edge-Aware Depth Image Filtering using color segmentation, ”Pattern Recognition Letters, Available online, 2014.

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以深度圖像修補為基礎之3D建模

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