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.

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