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GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS

Abstract: 

High-quality depth sensing is highly demanded in intelligent computer vision, 3DTV, and many other related fields. However, prevalent time-of-fly (ToF) depth sensors are of low resolution as the number of pixel-level demodulators is limited. Moreover, the rectangular sampling does not consider the signal characteristics of depth maps. Being a departure of previous resolution enhancement on rectangular sampling, this paper investigates the non-uniform sampling of depth maps, and the high-resolution depth reconstruction from limited non-uniformly distributed samples. The proposed depth sampling and reconstruction schemes are developed based on graph signal processing. We first propose a graph-based non-uniform sampling (GNS) scheme, where depth signals are sampled based on the response of a high-pass graph filter, which results in denser sampling around discontinuities such as edges and contours than in smooth regions. We then propose a graph-based depth reconstruction (GDR) framework,where a graph Laplacian regularizer is designed to fully exploit structural correlation between the depth and photometric images. To solve the reconstruction problem, we derive an efficient algorithm based on the alternating direction method of multipliers (ADMM). Experimental results show that the GNS-GDR non-uniform sampling and reconstruction method achieves high-quality depth sensing, outperforming several state-of-the-art schemes.

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Paper Details

Authors:
Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li
Submitted On:
20 September 2019 - 3:02am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Jingyu Yang
Paper Code:
3797
Document Year:
2019
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Jingyu Yang_2019icip

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[1] Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li, "GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4761. Accessed: Oct. 18, 2019.
@article{4761-19,
url = {http://sigport.org/4761},
author = {Jingyu Yang ; Xinchen Ye ; Pascal Frossard ; Kun Li },
publisher = {IEEE SigPort},
title = {GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS},
year = {2019} }
TY - EJOUR
T1 - GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS
AU - Jingyu Yang ; Xinchen Ye ; Pascal Frossard ; Kun Li
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4761
ER -
Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li. (2019). GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS. IEEE SigPort. http://sigport.org/4761
Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li, 2019. GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS. Available at: http://sigport.org/4761.
Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li. (2019). "GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS." Web.
1. Jingyu Yang , Xinchen Ye , Pascal Frossard , Kun Li. GRAPH BASED NON-UNIFORM SAMPLING AND RECONSTRUCTION OF DEPTH MAPS [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4761