Ego-Action Analysis for First-Person Sports Videos
Magazine Article, IEEE Pervasive Computing, Vol. 11, No. 2, pp. 92 - 95, February, 2012
Abstract
A new algorithm enables a fully automatic real-time video segmentation solution for dynamic first-person sports videos. The proposed approach leverages the latest in robust vision-based ego-motion estimation and unsupervised learning using nonparametric Bayesian modeling.
BibTeX
@periodical{Kitani-2012-109863,author = {Kris M. Kitani},
title = {Ego-Action Analysis for First-Person Sports Videos},
journal = {IEEE Pervasive Computing},
year = {2012},
month = {February},
pages = {92 - 95},
volume = {11},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.