Paper
13 May 2019 Vision based pointing error estimation for mobile eye-tracking system
Author Affiliations +
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shishir Paramathma Rao, Qianwen Wan, Karen Panetta, Sos Agaian, Aleksandra Kaszowska, and Holly A. Taylor "Vision based pointing error estimation for mobile eye-tracking system", Proc. SPIE 10993, Mobile Multimedia/Image Processing, Security, and Applications 2019, 109930Q (13 May 2019); https://doi.org/10.1117/12.2519259
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KEYWORDS
Panoramic photography

Eye

Error analysis

Analytical research

Cameras

Image processing

Video

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