Name
Title | ||
|---|---|---|
What do you want to do next: a novel approach for intent prediction in gaze-based interaction |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2168556.2168569 | ETRA |
Keywords | Field | DocType |
evaluation metrics,novel approach,task-independent prediction,biometric person authentication,normalization method,different feature set,interaction intent,gaze-based interaction,interaction intent prediction,multiple feature type,midas touch,machine learning,area under curve,feature extraction,eye tracking | Data mining,Computer vision,Normalization (statistics),Authentication,Gaze,Computer science,Activity detection,Artificial intelligence,Biometrics,Machine learning | Conference |
Citations | PageRank | References |
39 | 1.56 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roman Bednarik | 1 | 561 | 48.77 |
| Hana Vrzakova | 2 | 62 | 11.41 |
| Michal Hradis | 3 | 132 | 14.19 |