Year: 2025
Type: article
Abstract: In China, the rapid development of public transportation network construction has been accompanied by a high incidence of traffic accidents caused by sleep-deprived driving. The monitoring of drivers' sleep-deprived driving and the sending out of early warnings has been identified as a field of research with both important theoretical and practical value. This article proposes a fatigue detection algorithm based on facial recognition information fusion. The algorithm extracts facial feature information and head features from the driver's face and fuses them into facial recognition information parameter feature vectors. A set of feature nodes is thus constructed, and an information fusion feature map is constructed according to the interaction information between nodes. The fatigue status is detected using the label propagation strategy, which is more effective than other benchmark detection algorithms. The fatigue detection algorithm has practical value.
Source: Thermal Science
DOI: 10.2298/tsci2503007y
Author: Bin Yuan
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $161
OpenAlex ID: W4411454925