Vinay Bettadapura

Google, Inc.

College of Computing, Georgia Tech

vinay [at] gatech.edu

Irfan Essa

Google, Inc.

College of Computing, Georgia Tech

irfan [at] cc.gatech.edu

Caroline Pantofaru

Google Inc.

cpantofaru [at] google.com

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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@inproceedings{Bettadapura:2015:EgocentricLocalization,
       Author = {Vinay Bettadapura and Irfan Essa and Caroline Pantofaru},
       Booktitle = {Proceedings of IEEE Winter Conference on Applications of Computer Vision (WACV)},
       Month = {January},
       Organization = {IEEE},
       Title = {Egocentric Field-of-View Localization Using First-Person Point-of-View Devices},
       Year = {2015}
}

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