Time-Mapping Using Space-Time Saliency - Robotics Institute Carnegie Mellon University

Time-Mapping Using Space-Time Saliency

Feng Zhou, Sing Bing Kang, and Michael F. Cohen
Conference Paper, Proceedings of (CVPR) Computer Vision and Pattern Recognition, pp. 3358 - 3365, June, 2014

Abstract

We describe a new approach for generating regularspeed, low-frame-rate (LFR) video from a high-frame-rate (HFR) input while preserving the important moments in the original. We call this time-mapping, a time-based analogy to high dynamic range to low dynamic range spatial tone-mapping. Our approach makes these contributions: (1) a robust space-time saliency method for evaluating visual importance, (2) a re-timing technique to temporally resample based on frame importance, and (3) temporal filters to enhance the rendering of salient motion. Results of our space-time saliency method on a benchmark dataset show it is state-of-the-art. In addition, the benefits of our approach to HFR-to-LFR time-mapping over more direct methods are demonstrated in a user study.

BibTeX

@conference{Zhou-2014-7875,
author = {Feng Zhou and Sing Bing Kang and Michael F. Cohen},
title = {Time-Mapping Using Space-Time Saliency},
booktitle = {Proceedings of (CVPR) Computer Vision and Pattern Recognition},
year = {2014},
month = {June},
pages = {3358 - 3365},
}