2020/05/29 by Vasiliki Kondyli, Kondyli, Vasiliki, Mehul Bhatt +3 · 1 citation
Computer Science · Medicine · Neuroscience · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Technology and Human Factors in Education and Health #Visual Attention and Saliency Detection #Visual perception and processing mechanisms #cs.AI #cs.CV #cs.HC
paper · pdf · doi:10.48550/arxiv.2006.00059
9th European Starting AI Researchers Symposium (STAIRS), at ECAI 2020, the 24th European Conference on Artificial Intelligence (ECAI)., Santiago de Compostela, Spain
openalex publication_date 2020/05/29 · arxiv created 2020/06/02 · arxiv updated 2020/06/03 · openalex created_date 2020/06/05 · openalex updated_date 2026/07/28
We develop a human-centred, cognitive model of visuospatial complexity in everyday, naturalistic driving conditions. With a focus on visual perception, the model incorporates quantitative, structural, and dynamic attributes identifiable in the chosen context; the human-centred basis of the model lies in its behavioural evaluation with human subjects with respect to psychophysical measures pertaining to embodied visuoauditory attention. We report preliminary steps to apply the developed cognitive model of visuospatial complexity for human-factors guided dataset creation and benchmarking, and for its use as a semantic template for the (explainable) computational analysis of visuospatial complexity.