2015 CVPR CVPR 2015

Light Field From Micro-Baseline Image Pair

Abstract

We present a novel phase-based approach for recon- structing 4D light field from a micro-baseline stereo (LfS) pair. Our approach takes advantage of the unique prop- erty of complex steerable pyramid filters in micro-baseline stereo. We first introduce a disparity assisted phase based synthesis (DAPS) strategy that can integrate disparity infor- mation into the phase term of a reference image to warp it to its close neighbor views. Based on the DAPS, an "analy- sis by synthesis" approach is proposed to warp from one of the input binocular images to the other, and iteratively op- timize the disparity map to minimize the phase differences between the warped one and the ground truth input. Fi- nally, the densely and regularly spaced, high quality light field images can be reconstructed using the proposed DAPS according to the refined disparity map. Our approach also solves the problems of disparity inconsistency and ringing artifact in available phase-based view synthesis methods. Experimental results demonstrate that our approach sub- stantially improves both the quality of disparity map and light field, compared with the state-of-the-art stereo match- ing and image based rendering approaches.

🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning
🧭 Keyword Pioneer — phase synthesis
🐣 Hot Topic Early Bird — view synthesis
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics