Egocentric Field-of-View Localization Using First-Person Point-of-View Devices
Venue
Proceedings of Winter Conference on Applications of Computer Vision (WACV), IEEE (2015)
Publication Year
2015
Authors
Vinay Bettadapura, Irfan Essa, Caroline Pantofaru
BibTeX
Abstract
We present a technique that uses images, videos and sensor data taken from
first-person point-of-view devices to perform egocentric field-of-view (FOV)
localization. We define egocentric FOV localization as capturing the visual
information from a person’s field-of-view in a given environment and transferring
this information onto a reference corpus of images and videos of the same space,
hence determining what a person is attending to. Our method matches images and
video taken from the first-person perspective with the reference corpus and refines
the results using the first-person’s head orientation information obtained using
the device sensors. We demonstrate single and multi-user egocentric FOV
localization in different indoor and outdoor environments with applications in
augmented reality, event understanding and studying social interactions.
