Mapping of 3d Eye-Tracking in Urban Outdoor Environments

Abstract

Abstract. New geospatial technologies and ubiquitous sensing allow new insights into people’s spatial practices and experiences of public spaces. These tools offer new data streams for analysis and interpretation of social phenomena. Mobile augmented reality tools such as smartphones and wearables merge the experience of entangled online and offline spaces in citizen’s daily life. This paper demonstrates a concept that combines eye-tracking tools with innovative mapping in order to enhance the interpretability of real outdoor environmental experiences. Through videogrammetry, a participants’ head posture can be reconstructed. Subsequently the fixations measured through eye-tracking are projected onto a 3D point cloud of the surrounding environment. The presented methodological approach is implemented in the interdisciplinary project DigitAS – The Digital, Affects and Space – which investigates the perception of public places as spaces of recreation, security or fear. The project’s Mixed Methods approach combined qualitative, mobile, in-situ and reconstructive methods with eye-tracking in an outdoor setting. Potentials of the geospatial mapping concept for social science research is discussed.

MAP3D: An explorative approach for automatic mapping of real-world eye-tracking data on a virtual 3D model

“…In our third evaluation, we paid more attention to uniform lighting conditions and the reference images were taken in landscape format to match the world camera resulting in an improved matching in VisualSfM with all fixations being automatically mapped to the 3D model with the Fixa-tionProjector tool. Kollert et al (2021) also noted in their study that the pure use of eye-tracking frames can be insufficient for the creation of a 3D model. Therefore, they used an additional LiDAR scanner, further images, and they incorporated manual refinements to achieve their intended result.…”

“…The software they recommend for creating a 3D point cloud for the 3D model is commercial and therefore not freely available to researchers. Kollert et al (2021) used the technique of videoand photogrammetry in combination with eye tracking in their study, in which they recorded eye movements in urban outdoor environments. They created 3D heat maps by using a Tobii eye tracker and commercial software for the event detection and SfM technique.…”