
TL;DR
This paper explores the relationship between egocentric and top-view videos by developing a spectral graph matching approach to verify viewer presence and identify egocentric observers within top-view footage, even with unknown time delays.
Contribution
It introduces a novel spectral graph matching framework to jointly estimate viewer correspondence and time delays between egocentric and top-view videos.
Findings
Successfully localizes egocentric viewers in top-view videos.
Handles unknown time delays between videos.
Provides a method for verifying viewer presence across different viewpoints.
Abstract
Thanks to the availability and increasing popularity of Egocentric cameras such as GoPro cameras, glasses, and etc. we have been provided with a plethora of videos captured from the first person perspective. Surveillance cameras and Unmanned Aerial Vehicles(also known as drones) also offer tremendous amount of videos, mostly with top-down or oblique view-point. Egocentric vision and top-view surveillance videos have been studied extensively in the past in the computer vision community. However, the relationship between the two has yet to be explored thoroughly. In this effort, we attempt to explore this relationship by approaching two questions. First, having a set of egocentric videos and a top-view video, can we verify if the top-view video contains all, or some of the egocentric viewers present in the egocentric set? And second, can we identify the egocentric viewers in the content…
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