Towards the quantitative evaluation of visual attention models

Vision Research

Volumn 116, Issue , 2015, Pages 258-268

  Bylinskii, Z ^a,b   DeGennaro, E M ^c   Rajalingham, R ^d   Ruda, H ^e   Zhang, J ^f,g   Tsotsos, J K ^c,d,h  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Massachusetts Institute of Technology Cambridge   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^e NORTHEASTERN UNIVERSITY   (United States)

^f NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^g BRIGHAM AND WOMEN S HOSPITAL   (United States)

^h YORK UNIVERSITY   (Canada)

Author keywords

Benchmark datasets; Computational models; Evaluation; Model taxonomy; Opinion; Visual attention

Indexed keywords

ARTICLE; COMPARATIVE STUDY; ELECTROENCEPHALOGRAM; EYE MOVEMENT; GAZE; HUMAN; INFORMATION PROCESSING; LANGUAGE PROCESSING; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NORMAL DISTRIBUTION; ONLINE SYSTEM; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; QUALITY CONTROL; TAXONOMY; VISION; VISUAL ATTENTION; ANIMAL; ATTENTION; BIOLOGICAL MODEL; COMPUTER SIMULATION; PHYSIOLOGY;

ANIMALS; ATTENTION; COMPUTER SIMULATION; HUMANS; MODELS, NEUROLOGICAL; VISUAL PERCEPTION;

EID: 84946547780     PISSN: 00426989     EISSN: 18785646     Source Type: Journal    
DOI: 10.1016/j.visres.2015.04.007     Document Type: Article

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