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Vision based pointing error estimation for mobile eye-tracking system
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Paper Abstract

Translating environmental knowledge from bird’s eye view perspective, such as a map, to first person egocentric perspective is notoriously challenging, but critical for effective navigation and environment learning. Pointing error, or the angular difference between the perceived location and the actual location, is an important measure for estimating how well the environment is learned. Traditionally, errors in pointing estimates were computed by manually noting the angular difference. With the advent of commercial low-cost mobile eye trackers, it becomes possible to couple the advantages of automated image processing based techniques with these spatial learning studies. This paper presents a vision based analytic approach for calculating pointing error measures in real-world navigation studies relying only on data from mobile eye tracking devices. The proposed method involves three steps: panorama generation, probe image localization using feature matching, and navigation pointing error estimation. This first-of-its-kind application has game changing potential in the field of cognitive research using eye-tracking technology for understanding human navigation and environment learning and has been successfully adopted by cognitive psychologists.

Paper Details

Date Published: 13 May 2019
PDF: 11 pages
Proc. SPIE 10993, Mobile Multimedia/Image Processing, Security, and Applications 2019, 109930Q (13 May 2019); doi: 10.1117/12.2519259
Show Author Affiliations
Shishir Paramathma Rao, Tufts Univ. (United States)
Qianwen Wan, Tufts Univ. (United States)
Karen Panetta, Tufts Univ. (United States)
Sos Agaian, The City Univ. of New York (United States)
Aleksandra Kaszowska, Tufts Univ. (United States)
Holly A. Taylor, Tufts Univ. (United States)


Published in SPIE Proceedings Vol. 10993:
Mobile Multimedia/Image Processing, Security, and Applications 2019
Sos S. Agaian; Vijayan K. Asari; Stephen P. DelMarco, Editor(s)

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