Cristin-resultat-ID: 1977121
Sist endret: 9. januar 2022, 23:55
Resultat
Faglig foredrag
2021

Image Statistics as Glossiness and Translucency Predictor in Photographs of Real-world Objects

Bidragsytere:
  • Davit Gigilashvili

Presentasjon

Navn på arrangementet: NOBIM 2021
Sted: Gardermoen
Dato fra: 13. september 2021
Dato til: 14. september 2021

Arrangør:

Arrangørnavn: Norwegian Society for Image Processing and Machine Learning

Om resultatet

Faglig foredrag
Publiseringsår: 2021

Beskrivelse Beskrivelse

Tittel

Image Statistics as Glossiness and Translucency Predictor in Photographs of Real-world Objects

Sammendrag

We interpret our surrounding based on the visual stimuli, and perceive objects and materials around us to have various attributes, like color, glossiness, and translucency. We analyze the three-dimensional world based on the two-dimensional images detected by our retina. The state-of-the-art works conclude that the human visual system has a poor ability to fully understand and invert the complex optical nature of light and matter interaction. Some authors rather propose that the human brain calculates image statistics to perceive appearance, demonstrating correlation between perceptual attributes and various statistical metrics. However, the illustrated examples are usually unrealistic nearly-perfect stimuli, making real-life robustness of the findings questionable. In this study, we analyzed image statistics of photos of real world objects, and assessed the performance of statistical image metrics proposedly used by the human visual system. We identified very interesting trends, as well as limitations.

Bidragsytere

Davit Gigilashvili

  • Tilknyttet:
    Forfatter
    ved Institutt for datateknologi og informatikk ved Norges teknisk-naturvitenskapelige universitet
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