Dynamic programming algorithm optimization for spoken word recognition
Readings in speech recognition
The use of eye movements in human-computer interaction techniques: what you look at is what you get
ACM Transactions on Information Systems (TOIS) - Special issue on computer—human interaction
Machine Learning
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Twenty years of eye typing: systems and design issues
ETRA '02 Proceedings of the 2002 symposium on Eye tracking research & applications
The Case against Accuracy Estimation for Comparing Induction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Task-evoked pupillary response to mental workload in human-computer interaction
CHI '04 Extended Abstracts on Human Factors in Computing Systems
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Transactions on Computer-Human Interaction (TOCHI)
Snap clutch, a moded approach to solving the Midas touch problem
Proceedings of the 2008 symposium on Eye tracking research & applications
Can eyes reveal interest? Implicit queries from gaze patterns
User Modeling and User-Adapted Interaction
Inferring object relevance from gaze in dynamic scenes
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Towards task-independent person authentication using eye movement signals
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Fixation-aligned pupillary response averaging
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Skim reading by satisficing: evidence from eye tracking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Cognitive Systems Research
Modeling video viewing behaviors for viewer state estimation
Proceedings of the 20th ACM international conference on Multimedia
Hard lessons learned: mobile eye-tracking in cockpits
Proceedings of the 4th Workshop on Eye Gaze in Intelligent Human Machine Interaction
Proceedings of the 4th Workshop on Eye Gaze in Intelligent Human Machine Interaction
Semantic interpretation of eye movements using designed structures of displayed contents
Proceedings of the 4th Workshop on Eye Gaze in Intelligent Human Machine Interaction
Computational approaches to visual attention for interaction inference
Proceedings of the companion publication of the 2013 international conference on Intelligent user interfaces companion
Inferential methods in interaction, usability and user experience
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Multimodal smart interactive presentation system
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
Modeling semantic aspects of gaze behavior while catalog browsing
Proceedings of the 15th ACM on International conference on multimodal interaction
Learning aspects of interest from Gaze
Proceedings of the 6th workshop on Eye gaze in intelligent human machine interaction: gaze in multimodal interaction
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Interaction intent prediction and the Midas touch have been a longstanding challenge for eye-tracking researchers and users of gaze-based interaction. Inspired by machine learning approaches in biometric person authentication, we developed and tested an offline framework for task-independent prediction of interaction intents. We describe the principles of the method, the features extracted, normalization methods, and evaluation metrics. We systematically evaluated the proposed approach on an example dataset of gaze-augmented problem-solving sessions. We present results of three normalization methods, different feature sets and fusion of multiple feature types. Our results show that accuracy of up to 76% can be achieved with Area Under Curve around 80%. We discuss the possibility of applying the results for an online system capable of interaction intent prediction.