Abstract
The recent development of light field cameras has received growing interest, as their rich angular information has potential benefits for many computer vision tasks. In this paper, we introduce a novel method to obtain a dense disparity map by use of ground control points (GCPs) in the light field. Previous work optimizes the disparity map by local estimation which includes both reliable points and unreliable points. To reduce the negative effect of the unreliable points, we predict the disparity at non-GCPs from GCPs. Our method performs more robustly in shadow areas than previous methods based on GCP work, since we combine color information and local disparity. Experiments and comparisons on a public dataset demonstrate the effectiveness of our proposed method.
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Hao Zhu received his B.E. degree from the School of Computer Science, Northwestern Polytechnic University, in 2014. He is now a Ph.D. candidate in the School of Computer Science, Northwestern Polytechnic University. His research interests include computational photography and computer vision.
Qing Wang is a professor and Ph.D. tutor in the School of Computer Science, Northwestern Polytechnic University. He graduated from the Department of Mathematics, Peking University, in 1991. He then joined Northwestern Polytechnic University as a lecturer. In 1997 and 2000 he obtained his master and Ph.D. degrees from the Department of Computer Science and Engineering, Northwestern Polytechnic University, respectively. In 2006, he was recognized by the Outstanding Talent of the New Century Program by the Ministry of Education, China. He is a member of IEEE and ACM. He is also a senior member of the China Computer Federation (CCF).
He worked as a research assistant and research scientist in the Department of Electronic and Information Engineering, Hong Kong Polytechnic University, from 1999 to 2002. He also worked as a visiting scholar in the School of Information Engineering, University of Sydney, in 2003 and 2004. In 2009 and 2012, he visited the Human Computer Interaction Institute, Carnegie Mellon University, for six months, and the Department of Computer Science, University of Delaware, for one month, respectively.
Prof. Wang’s research interests include computer vision and computational photography, including 3D structure and shape reconstruction, object detection, tracking and recognition in dynamic environments, and light field imaging and processing. He has published more than 100 papers in international journals and conferences.
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Zhu, H., Wang, Q. Accurate disparity estimation in light field using ground control points. Comp. Visual Media 2, 173–181 (2016). https://doi.org/10.1007/s41095-016-0052-6
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DOI: https://doi.org/10.1007/s41095-016-0052-6