Title :
TOF Depth Map Super-resolution Using Compressive Sensing
Author :
Li-Wei Liu ; Yang Li ; Liang-Hao Wang ; Dong-Xiao Li ; Ming Zhang
Author_Institution :
Inst. of Inf. & Commun. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
Although Time-of-Flight (TOF) camera can provide real-time depth information from a real scene, the resolution of depth map captured by TOF camera is rather limited compared to HD color cameras, and thus it cannot be directly used in 3D reconstruction. In order to handle this problem, this paper proposes a novel compressive sensing (CS) based depth map super-resolution method, which transforms a low resolution depth map to a high resolution depth map. Different from previous depth map SR methods, this algorithm uses a model-based CS as reconstruction theory, and this method also builds a TOF camera sampling model which is used in depth map SR. Experimental results show that the proposed method outperforms state-of-the-art methods for depth map super-resolution.
Keywords :
cameras; compressed sensing; image reconstruction; image resolution; 3D reconstruction; CS based depth map super-resolution method; HD color cameras; TOF camera sampling model; TOF depth map super-resolution; compressive sensing; high resolution depth map; low resolution depth map; realtime depth information; reconstruction theory; time-of-flight depth map super-resolution; Cameras; Compressed sensing; Image reconstruction; Image resolution; Signal resolution; Sparse matrices; Vectors; Time-of-Flight camera; compressive sensing; depth; super-resolution;
Conference_Titel :
Image and Graphics (ICIG), 2013 Seventh International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ICIG.2013.33