Integrating Egocentric Videos in Top-view Surveillance
Videos: Joint Identification and Temporal Alignment
Abstract. Videos recorded from first person (egocentric) perspective have little
visual appearance in common with those from third person perspective, especially with videos captured by top-view surveillance cameras. In this paper, we
aim to relate these two sources of information from a surveillance standpoint,
namely in terms of identification and temporal alignment. Given an egocentric
video and a top-view video, our goals are to: a) identify the egocentric camera
holder in the top-view video (self-identification), b) identify the humans visible
in the content of the egocentric video, within the content of the top-view video
(re-identification), and c) temporally align the two videos. The main challenge is
that each of these tasks is highly dependent on the other two. We propose a uni-
fied framework to jointly solve all three problems. We evaluate the efficacy of the
proposed approach on a publicly available dataset containing a variety of videos
recorded in different scenarios