3D gaze estimation from 2D pupil positions on monocular head-mounted eye
trackers
Poster abstracts
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Mansourya, Mohsen
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Steil, Julian
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Sugano, Yusuke
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Bulling, Andreas
Proceedings of the 2016 Symposium on Eye Tracking Research &
Applications
2016-03-14
p.197-200
© Copyright 2016 ACM
Summary: 3D gaze information is important for scene-centric attention analysis, but
accurate estimation and analysis of 3D gaze in real-world environments remains
challenging. We present a novel 3D gaze estimation method for monocular
head-mounted eye trackers. In contrast to previous work, our method does not
aim to infer 3D eyeball poses, but directly maps 2D pupil positions to 3D gaze
directions in scene camera coordinate space. We first provide a detailed
discussion of the 3D gaze estimation task and summarize different methods,
including our own. We then evaluate the performance of different 3D gaze
estimation approaches using both simulated and real data. Through experimental
validation, we demonstrate the effectiveness of our method in reducing parallax
error, and we identify research challenges for the design of 3D calibration
procedures.
Discovery of everyday human activities from long-term visual behaviour using
topic models
Quantifying and communicating through wearables
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Steil, Julian
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Bulling, Andreas
Proceedings of the 2015 International Conference on Ubiquitous Computing
2015-09-07
p.75-85
© Copyright 2015 ACM
Summary: Human visual behaviour has significant potential for activity recognition
and computational behaviour analysis, but previous works focused on supervised
methods and recognition of predefined activity classes based on short-term eye
movement recordings. We propose a fully unsupervised method to discover users'
everyday activities from their long-term visual behaviour. Our method combines
a bag-of-words representation of visual behaviour that encodes saccades,
fixations, and blinks with a latent Dirichlet allocation (LDA) topic model. We
further propose different methods to encode saccades for their use in the topic
model. We evaluate our method on a novel long-term gaze dataset that contains
full-day recordings of natural visual behaviour of 10 participants (more than
80 hours in total). We also provide annotations for eight sample activity
classes (outdoor, social interaction, focused work, travel, reading, computer
work, watching media, eating) and periods with no specific activity. We show
the ability of our method to discover these activities with performance
competitive with that of previously published supervised methods.
An assistance system for guiding workers in central sterilization supply
departments
Rehabilitation robotics and multimodal interfaces
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Rüther, Stefan
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Hermann, Thomas
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Mracek, Maik
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Kopp, Stefan
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Steil, Jochen
Proceedings of the 2013 International Conference on PErvasive Technologies
Related to Assistive Environments
2013-05-29
p.3
© Copyright 2013 ACM
Summary: The reprocessing of medical devices is an essential process to keep a
hospital functional. It is carried out in the Central Sterilization Supply
Department (CSSD). Failures during reprocessing can endanger patients' safety
and increase costs. The benefits of an assistance system helping workers in
preventing failures are therefore obvious, whereas challenging requirements
arise through process complexity, legislation, integration and hygiene
restrictions. We propose an assistance system that supports the worker in the
unclean area of a CSSD under these requirements. It provides a user interface
for context-aware guidance and collection of process relevant data from the
worker. 'Virtual touches' fulfill the hygiene requirements and are realized
with a depth camera and a projected user interface. Business process models
control the workflow and maintain a valid database for quality assurance and
worker guidance. We evaluated the system with a user study focusing on failure
prevention, task completion time and usability.
