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Volumn 2, Issue , 2010, Pages 370-375

Real-time enhancement of image and video saliency using semantic depth of field

Author keywords

Attention guidance; Importance maps; Saliency maps; Semantic depth of field; Visual attention

Indexed keywords

ATTENTION GUIDANCE; DEPTH OF FIELD; DYNAMIC SCENES; HUMAN VISUAL SYSTEM; IMPORTANCE MAP; LOW-LEVEL FEATURES; LOW-LEVEL VISION; REAL TIME; SALIENCY MAPS; SPATIAL FILTERS; SPATIAL FREQUENCY; TEMPORAL FEATURES; TEMPORAL FILTERS; VISUAL ATTENTION;

EID: 77956311637     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (10)

References (17)
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    • Bayesian surprise attracts human attention
    • Itti, L. and Baldi, P. F. (2009). Bayesian surprise attracts human attention. Vision Research, 49(10): 1295-1306.
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    • Itti, L.1    Baldi, P.F.2
  • 7
    • 0035286497 scopus 로고    scopus 로고
    • Computational modelling of visual attention
    • Itti, L. and Koch, C. (2001). Computational modelling of visual attention. Nature Reviews Neuroscience, 2(3): 194-203.
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    • Itti, L.1    Koch, C.2
  • 9
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    • Shifts in selective visual attention: Towards the underlying neural circuitry
    • Koch, C. and Ullman, S. (1985). Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiology, 4(4):219-227.
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    • Koch, C.1    Ullman, S.2
  • 14
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    • Current approaches to change blindness
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    • Simons, D.J.1
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    • Analyzing vision at the complexity level
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    • Tsotsos, J.1
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    • SUN: A Bayesian framework for saliency using natural statistics
    • Zhang, L., Tong, M. H., Marks, T. K., Shan, H., and Cottrell, G. W. (2008). SUN: A Bayesian framework for saliency using natural statistics. Journal of Vision, 8(7): 1-20.
    • (2008) Journal of Vision , vol.8 , Issue.7 , pp. 1-20
    • Zhang, L.1    Tong, M.H.2    Marks, T.K.3    Shan, H.4    Cottrell, G.W.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.