Among the different personality traits that guide our behaviour, curiosity is particularly interesting for context-aware assistive systems as it is closely linked to our well-being and the way we learn. This work proposes eye movement analysis for automatic recognition of different levels of curiosity. We present a 26-participant gaze dataset recorded during a real-world shopping task with empirically validated curiosity questionnaires as ground truth. Using a support vector machine classifier and a leave-one-person-out evaluation scheme we can discriminate between two to four classes of standard curiosity scales well above chance. These results are promising and point towards a new class of context-aware systems that take the user's curiosity into account, thereby enabling new types of interaction and user adaptation.
|Number of pages||4|
|Publication status||Published - 2015|
|Event||ACM International Joint Conference on Pervasive and Ubiquitous Computing - |
Duration: 7 Sep 2015 → …
|Conference||ACM International Joint Conference on Pervasive and Ubiquitous Computing|
|Period||7/09/15 → …|