Adaptive Temporal Compressive Sensing for Video
Applications
2016-11-17 v3 Computer Vision and Pattern Recognition
Multimedia
Abstract
This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to real-time implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.
Cite
@article{arxiv.1302.3446,
title = {Adaptive Temporal Compressive Sensing for Video},
author = {Xin Yuan and Jianbo Yang and Patrick Llull and Xuejun Liao and Guillermo Sapiro and David J. Brady and Lawrence Carin},
journal= {arXiv preprint arXiv:1302.3446},
year = {2016}
}
Comments
IEEE Interonal International Conference on Image Processing (ICIP),2013