3D gaze point localization and visualization using LiDAR-based 3D
reconstructions
Video & demo abstracts
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Pieszala, James
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Diaz, Gabriel
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Pelz, Jeff
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Speir, Jacqueline
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Bailey, Reynold
Proceedings of the 2016 Symposium on Eye Tracking Research &
Applications
2016-03-14
p.201-204
© Copyright 2016 ACM
Summary: We present a novel pipeline for localizing a free roaming eye tracker within
a LiDAR-based 3D reconstructed scene with high levels of accuracy. By utilizing
a combination of reconstruction algorithms that leverage the strengths of
global versus local capture methods and user-assisted refinement, we reduce
drift errors associated with Dense-SLAM techniques. Our framework supports
region-of-interest (ROI) annotation and gaze statistics generation and the
ability to visualize gaze in 3D from an immersive first person or third person
perspective. This approach gives unique insights into viewers' problem solving
and search task strategies and has high applicability in complex static
environments such as crime scenes.