EgoSampling: Fast-Forward and Stereo for Egocentric Videos

Yair Poleg, Tavi Halperin, Chetan Arora, Shmuel Peleg; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 4768-4776

Abstract


While egocentric cameras like GoPro are gaining popularity, the videos they capture are long, boring, and difficult to watch from start to end. Fast forwarding (i.e. frame sampling) is a natural choice for faster video browsing. However, this accentuates the shake caused by natural head motion, making the fast forwarded video useless. We propose EgoSampling, an adaptive frame sampling that gives more stable fast forwarded videos. Adaptive frame sampling is formulated as energy minimization, whose optimal solution can be found in polynomial time. In addition, egocentric video taken while walking suffers from the left-right movement of the head as the body weight shifts from one leg to another. We turn this drawback into a feature: Stereo video can be created by sampling the frames from the left most and right most head positions of each step, forming approximate stereo-pairs.

Related Material


[pdf]
[bibtex]
@InProceedings{Poleg_2015_CVPR,
author = {Poleg, Yair and Halperin, Tavi and Arora, Chetan and Peleg, Shmuel},
title = {EgoSampling: Fast-Forward and Stereo for Egocentric Videos},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}