HandyGaze: A Gaze Tracking Technique for Room-Scale Environments using a Single Smartphone
We propose HandyGaze, a 6-DoF gaze tracking technique for room-scale environments that can be carried out by simply holding a smartphone naturally without installing any sensors or markers in the environment. Our technique simultaneously employs the smartphone's front and rear cameras: The front camera estimates the user's gaze vector relative to the smartphone, while the rear camera (and depth sensor, if available) performs self-localization by reconstructing a pre-obtained 3D map of the environment.
To achieve this, we implemented a prototype that works on iOS smartphones by running an ARKit-based algorithm for estimating the user's 6-DoF head orientation. We additionally implemented a novel calibration method that offsets the user-specific deviation between the head and gaze orientations.
We then conducted a user study (N=10) that measured our technique's positional accuracy to the gaze target under four conditions, based on combinations of use with and without a depth sensor and calibration. The results show that our calibration method was able to reduce the mean absolute error of the gaze point by $27%$, with an error of 0.53,m when using the depth sensor. We also report the target size required to avoid erroneous inputs. Finally, we suggest possible applications such as a gaze-based guidance application for museums.
Mon 21 NovDisplayed time zone: Auckland, Wellington change
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PapersDOI Media Attached
|HandyGaze: A Gaze Tracking Technique for Room-Scale Environments using a Single Smartphone
Takahiro Nagai Tohoku University, Kazuyuki Fujita Tohoku University, Kazuki Takashima Tohoku University, Yoshifumi Kitamura Tohoku UniversityDOI Media Attached
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Jiazhou Liu Monash University, Arnaud Prouzeau Inria & LaBRI (University of Bordeaux, CNRS, Bordeaux-INP), Barrett Ens Monash University, Tim Dwyer Monash UniversityDOI Media Attached