AFFECTIVE COMPUTING AND AUGMENTED REALITY FOR CAR DRIVING SIMULATORS
dc.contributor.author | Datcu, Dragoș | |
dc.contributor.author | Rothkrantz, Leon | |
dc.date.accessioned | 2023-01-18T14:54:15Z | |
dc.date.available | 2023-01-18T14:54:15Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Acta Polytechnica. 2017, vol. 12, no. 0, p. 13-23. | |
dc.identifier.issn | 1210-2709 (print) | |
dc.identifier.issn | 1805-2363 (online) | |
dc.identifier.uri | http://hdl.handle.net/10467/105946 | |
dc.description.abstract | Car simulators are essential for training and for analyzing the behavior, the responses and the performance of the driver. Augmented Reality (AR) is the technology that enables virtual images to be overlaid on views of the real world. Affective Computing (AC) is the technology that helps reading emotions by means of computer systems, by analyzing body gestures, facial expressions, speech and physiological signals. The key aspect of the research relies on investigating novel interfaces that help building situational awareness and emotional awareness, to enable affect-driven remote collaboration in AR for car driving simulators. The problem addressed relates to the question about how to build situational awareness (using AR technology) and emotional awareness (by AC technology), and how to integrate these two distinct technologies [4], into a unique affective framework for training, in a car driving simulator. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | České vysoké učení technické v Praze | cs |
dc.publisher | Czech Technical University in Prague | en |
dc.relation.ispartofseries | Acta Polytechnica | |
dc.relation.uri | https://ojs.cvut.cz/ojs/index.php/APP/article/view/4007 | |
dc.rights | Creative Commons Attribution 4.0 International License | en |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.title | AFFECTIVE COMPUTING AND AUGMENTED REALITY FOR CAR DRIVING SIMULATORS | |
dc.type | article | en |
dc.date.updated | 2023-01-18T14:54:15Z | |
dc.identifier.doi | 10.14311/APP.2017.12.0013 | |
dc.rights.access | openAccess | |
dc.type.status | Peer-reviewed | |
dc.type.version | publishedVersion |
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