[bibtex key= 2015-Bettadapura-EFLUFPD]
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.
- Additional Details from Egocentric FOV Localization
- Winner of the Best Paper Award
- Presented at IEEE Winter Conference on Application of Computer Vision (WACV) 2015, Waikoloa Beach, HI, January 6-9, 2015.