Abstract
Attention level estimation systems have a high potential in many use cases, such as human-robot interaction, driver modeling and smart home systems, since being able to measure a person’s attention level opens the possibility to natural interaction between humans and computers. The topic of estimating a human’s visual focus of attention has been actively addressed recently in the field of HCI. However, most of these previous works do not consider attention as a subjective, cognitive attentive state. New research within the field also faces the problem of the lack of annotated datasets regarding attention level in a certain context. The novelty of our work is two-fold: First, we introduce a new annotation framework that tackles the subjective nature of attention level and use it to annotate more than 100,000 images with three attention levels and second, we introduce a novel method to estimate attention levels, relying purely on extracted geometric features from RGB and depth images, and evaluate it with a deep learning fusion framework. The system achieves an overall accuracy of 80.02%. Our framework and attention level annotations are made publicly available.
Originalsprog | Engelsk |
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Titel | Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications : Volume 5: VISAPP |
Redaktører | Andreas Kerren, Christophe Hurter, Jose Braz |
Antal sider | 8 |
Vol/bind | 5 |
Forlag | SCITEPRESS Digital Library |
Publikationsdato | 2019 |
Sider | 249-256 |
ISBN (Trykt) | 978-989-758-354-4 |
ISBN (Elektronisk) | 9789897583544 |
DOI | |
Status | Udgivet - 2019 |
Begivenhed | 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Visigrapp 2019) - Prague, Tjekkiet Varighed: 25 feb. 2019 → 27 feb. 2019 |
Konference
Konference | 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Visigrapp 2019) |
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Land/Område | Tjekkiet |
By | Prague |
Periode | 25/02/2019 → 27/02/2019 |