Video Reflection Removal Through Spatio-Temporal Optimization
Name
video-reflection-removal-through-spatio-temporal-optimization-iccv-2017-nandoriya-et-al.pdf
Description
Accepted version
Size
1.39 MB
Format
Adobe PDF
Checksum (MD5)
30b8a8af4a9e85a27170d15c339096b4
Author(s)
Nandoriya, Ajay
Elgharib, Mohamed
Kim, Changil
Hefeeda, Mohamed
Matusik, Wojciech
Date Issued
October 2017
Publisher
IEEE
Citation
Nandoriya, Ajay, Elgharib, Mohamed, Kim, Changil, Hefeeda, Mohamed and Matusik, Wojciech. 2017. "Video Reflection Removal Through Spatio-Temporal Optimization."
Version
Author's final manuscript
Abstract
© 2017 IEEE. Reflections can obstruct content during video capture and hence their removal is desirable. Current removal techniques are designed for still images, extracting only one reflection (foreground) and one background layer from the input. When extended to videos, unpleasant artifacts such as temporal flickering and incomplete separation are generated. We present a technique for video reflection removal by jointly solving for motion and separation. The novelty of our work is in our optimization formulation as well as the motion initialization strategy. We present a novel spatiotemporal optimization that takes n frames as input and directly estimates 2n frames as output, n for each layer. We aim to fully utilize spatio-temporal information in our objective terms. Our motion initialization is based on iterative frame-to-frame alignment instead of the direct alignment used by current approaches. We compare against advanced video extensions of the state of the art, and we significantly reduce temporal flickering and improve separation. In addition, we reduce image blur and recover moving objects more accurately. We validate our approach through subjective and objective evaluations on real and controlled data.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/iccv.2017.264
