Paper in WACV (2015): “Egocentric Field-of-View Localization Using First-Person Point-of-View Devices”

Paper

V. Bettadapura, I. Essa, and Caroline Pantofaru (2015), “Egocentric Field-of-View Localization Using First-Person Point-of-View Devices,” in IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. (Best Paper Award) [PDF] [WEBSITE] [DOI] [arXiv] [BIBTEX]

@InProceedings{ 2015-Bettadapura-EFLUFPD,
arxiv = {http://arxiv.org/abs/1510.02073},
author  = {Vinay Bettadapura and Irfan Essa and Caroline
Pantofaru},
awards  = {(Best Paper Award)},
booktitle  = {{IEEE Winter Conference on Applications of Computer
Vision (WACV)}},
doi = {10.1109/WACV.2015.89},
month = {January},
pdf = {http://www.cc.gatech.edu/~irfan/p/2015-Bettadapura-EFLUFPD.pdf},
publisher  = {IEEE Computer Society},
title = {Egocentric Field-of-View Localization Using
First-Person Point-of-View Devices},
url = {http://www.vbettadapura.com/egocentric/localization/},
year = {2015}
}

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.