Toward Better Driving with Gaze Awareness Environment Supported by Area Segmentation
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| Title: | Toward Better Driving with Gaze Awareness Environment Supported by Area Segmentation |
|---|---|
| Language: | English |
| Authors: | Yamada, Taketo, Matsuura, Kenji, Takeuchi, Hironori, Kashihara, Akihiro, Yamasaki, Kenichi, Kurita, Genta, International Association for Development of the Information Society (IADIS) |
| Source: | International Association for Development of the Information Society. 2022Paper presented at the International Conference on Cognition and Exploratory Learning in Digital Age (CELDA) (19th, 2022). |
| Availability: | International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org |
| Peer Reviewed: | Y |
| Page Count: | 8 |
| Publication Date: | 2022 |
| Document Type: | Speeches/Meeting Papers Reports - Evaluative |
| Descriptors: | Motor Vehicles, Traffic Safety, Specialists, Comparative Analysis, Eye Movements, Skill Development, Artificial Intelligence, Learning Management Systems, Computer Simulation, Video Technology, Instructional Effectiveness, Feedback (Response), Teaching Methods |
| Abstract: | It is important to make car-drivers improve their way of looking for recognizing key objects or areas precisely. This study designs a system following such a motivation that distinguishes several areas in a display with weights of importance. A present proposing function for successful area detection offers drivers an opportunity to compare their gaze with experts. Concrete method for this implementation includes U-Net that is one of major techniques of machine learning combined with grid segmentation. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Accession Number: | ED626897 |
| Database: | ERIC |
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