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 unified 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.

Publication Date

1-1-2018

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

11215 LNCS

Number of Pages

300-317

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-030-01252-6_18

Socpus ID

85055089784 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85055089784

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