Depth reconstruction from sparse samples: representation, algorithm, and sampling

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Lee-Kang LiuTruong Q Nguyen

Abstract

The rapid development of 3D technology and computer vision applications has motivated a thrust of methodologies for depth acquisition and estimation. However, existing hardware and software acquisition methods have limited performance due to poor depth precision, low resolution, and high computational cost. In this paper, we present a computationally efficient method to estimate dense depth maps from sparse measurements. There are three main contributions. First, we provide empirical evidence that depth maps can be encoded much more sparsely than natural images using common dictionaries, such as wavelets and contourlets. We also show that a combined wavelet-contourlet dictionary achieves better performance than using either dictionary alone. Second, we propose an alternating direction method of multipliers (ADMM) for depth map reconstruction. A multiscale warm start procedure is proposed to speed up the convergence. Third, we propose a two-stage randomized sampling scheme to optimally choose the sampling locations, thus maximizing the reconstruction performance for a given sampling budget. Experimental results show that the proposed method produces high-quality dense depth estimates, and is robust to noisy measurements. Applica...Continue Reading

References

Dec 24, 2005·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Minh N Do, Martin Vetterli
Jun 13, 2006·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Duncan D Y Po, Minh N Do
Jan 31, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Julien MairalGuillermo Sapiro
Jan 17, 2009·IEEE Transactions on Pattern Analysis and Machine Intelligence·Qingxiong YangDavid Nistér
Jun 3, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Stanley H ChanTruong Q Nguyen
Aug 16, 2012·IEEE Transactions on Bio-medical Engineering·Ramsin KhoshabehTruong Q Nguyen
Dec 3, 2013·Science·Ahmed KirmaniVivek K Goyal
Aug 15, 2014·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Stanley H ChanYue M Lu
Mar 15, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Lee-Kang LiuTruong Q Nguyen

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Citations

Mar 15, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Lee-Kang LiuTruong Q Nguyen
Nov 11, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Srimanta MandalAnil Kumar Sao
Mar 31, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Li SunChun Chen
Apr 13, 2019·Sensors·Daniel Stanley TanKai-Lung Hua
Mar 18, 2020·Sensors·Haojie LiuMeiqin Liu
Dec 17, 2020·Optics Letters·Lingdong KongPeiheng Wu
Jun 3, 2021·Sensors·Miguel OliveiraVítor Santos

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