Real Time Complete Dense Depth Reconstruction for a Monocular Camera

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2016, pp. 674 - 679
Issue Date:
2016-10-05
Full metadata record
Files in This Item:
Filename Description Size
07789579.pdfPublished version660.63 kB
Adobe PDF
In this paper, we aim to solve the problem of estimating complete dense depth maps from a monocular moving camera. By 'complete', we mean depth information is estimated for every pixel and detailed reconstruction is achieved. Although this problem has previously been attempted, the accuracy of complete dense depth reconstruction is a remaining problem. We propose a novel system which produces accurate complete dense depth map. The new system consists of two subsystems running in separated threads, namely, dense mapping and sparse patch-based tracking. For dense mapping, a new projection error computation method is proposed to enhance the gradient component in estimated depth maps. For tracking, a new sparse patch-based tracking method estimates camera pose by minimizing a normalized error term. The experiments demonstrate that the proposed method obtains improved performance in terms of completeness and accuracy compared to three state-of the-art dense reconstruction methods VSFM+CMVC, LSDSLAM and REMODE.
Please use this identifier to cite or link to this item: