Given a video of an activity, can we predict what will happen next? In this paper we explore two simple tasks related to temporal prediction in egocentric videos of everyday activities. We provide both human experiments to understand how well people can perform on these tasks and computational models for prediction. Experiments indicate that humans and computers can do well on temporal prediction and that personalization to a particular individual or environment provides significantly increased performance. Developing methods for temporal prediction could have far reaching benefits for robots or intelligent agents to anticipate what a person will do, before they do it.


Temporal Perception and Prediction in Ego-Centric Video
Yipin Zhou and Tamara L. Berg
Proceedings of 15th IEEE International Conference on Computer Vision (ICCV2015)
[PDF 10MB]   [Poster 10MB]

   booktitle = {ICCV},
   year      = {2015},
   author    = {Yipin Zhou and Tamara L. Berg},
   title     = {Temporal Perception and Prediction in Ego-Centric Video},}


FPPA ego-centric dataset (6.8G) [README]
Please email yipin@cs.unc.edu to get the link for downloading.