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Author Veeraraghavan, S. ♦ Agrawal, A.
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Dynamic Scene ♦ Motion-aware Light Field Video ♦ Resolution Tradeoff ♦ High Resolution Lf Video ♦ Programmable Camera ♦ Scene-specific Redundancy ♦ Graphic Simulator ♦ Trade-off Spatial Resolution ♦ High Spatial Resolution Lf Video ♦ High Resolution Digital Refocusing ♦ Robust Reconstruction ♦ Motionaware Reconstruction Algorithm ♦ Novel Result ♦ Lf Video Camera ♦ Current Light Field ♦ Temporal Resolution ♦ Key Idea ♦ Realistic Simulation ♦ Real Result ♦ Tradeoff Temporal Resolution ♦ Extensive Analysis ♦ Local Motion-aware Adaptive Reconstruction ♦ Sparse Representation ♦ Single-shot Lf ♦ Dynamic Moving Object ♦ Static Scene ♦ Use Dictionary Learning ♦ High Spatial Resolution Lf
Abstract Current Light Field (LF) cameras offer fixed resolution in space, time and angle which is decided a-priori and is independent of the scene. These cameras either trade-off spatial resolution to capture single-shot LF [20, 27, 12] or tradeoff temporal resolution by assuming a static scene to capture high spatial resolution LF [18, 3]. Thus, capturing high spatial resolution LF video for dynamic scenes remains an open and challenging problem. We present the concept, design and implementation of a LF video camera that allows capturing high resolution LF video. The spatial, angular and temporal resolution are not fixed a-priori and we exploit the scene-specific redundancy in space, time and angle. Our reconstruction is motion-aware and offers a continuum of resolution tradeoff with increasing motion in the scene. The key idea is (a)to design efficient multiplexing matrices that allow resolution tradeoffs, (b) use dictionary learning and sparse representations for robust reconstruction, and (c) perform local motion-aware adaptive reconstruction. We perform extensive analysis and characterize the performance of our motionaware reconstruction algorithm. We show realistic simulations using a graphics simulator as well as real results using a LCoS based programmable camera. We demonstrate novel results such as high resolution digital refocusing for dynamic moving objects.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2013-01-01