Perceiving the representative surface color of real-world materials

被引:0
|
作者
Yan Zhang
Isamu Motoyoshi
机构
[1] The University of Tokyo,Department of Life Sciences
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Natural surfaces such as soil, grass, and skin usually involve far more complex and heterogenous structures than the perfectly uniform surfaces assumed in studies on color and material perception. Despite this, we can easily perceive the representative color of these surfaces. Here, we investigated the visual mechanisms underlying the perception of representative surface color using 120 natural images of diverse materials and their statistically synthesized images. Our matching experiments indicated that the perceived representative color revealed was not significantly different from the Portilla–Simoncelli-synthesized images or phase-randomized images except for one sample, even though the perceived shape and material properties were greatly impaired in the synthetic stimuli. The results also showed that the matched representative colors were predictable from the saturation-enhanced color of the brightest point in the image, excluding the high-intensity outliers. The results support the notion that humans judge the representative color and lightness of real-world surfaces depending on simple image measurements.
引用
收藏
相关论文
共 50 条
  • [41] Intrathecal catheterisation after accidental dural puncture: real-world data, real-world benefits and real-world barriers
    Broom, M. A.
    ANAESTHESIA, 2023, 78 (10) : 1195 - 1198
  • [42] Is the PARADIGM-HF cohort representative of the real-world heart failure patient population?
    Rodrigues, Gustavo
    Tralhao, Antonio
    Aguiar, Carlos
    Freitas, Pedro
    Ventosa, Antonio
    Mendes, Miguel
    REVISTA PORTUGUESA DE CARDIOLOGIA, 2018, 37 (06) : 491 - 496
  • [43] ITS A REAL REAL REAL-WORLD
    EVANS, RA
    IEEE TRANSACTIONS ON RELIABILITY, 1994, 43 (04) : 550 - 550
  • [44] Ibis: Real-World Problem Solving using Real-World Grids
    Bal, H. E.
    Drost, N.
    Kemp, R.
    Maassen, J.
    van Nieuwpoort, R. V.
    van Reeuwijk, C.
    Seinstra, F. J.
    2009 IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, VOLS 1-5, 2009, : 1831 - 1838
  • [45] Editorial: Real-world data and real-world evidence in lung cancer
    Gristina, Valerio
    Eze, Chukwuka
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [46] Inaccurate Real-World Data Does Not Provide Real-World Answers
    Buffet, Gabriela
    Mendoza-Sassi, Raul
    Fysekidis, Marinos
    AMERICAN JOURNAL OF THERAPEUTICS, 2021, 28 (05) : E596 - E598
  • [47] Editorial: Real-world data and real-world evidence in hematologic malignancies
    Malagola, Michele
    Ohgami, Robert
    Greco, Raffaella
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [48] Real-World Computer Vision for Real-World Applications: Challenges and Directions
    Tabkhi, Hamed
    INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, 2023, 542 : 727 - 750
  • [49] When can real-world data generate real-world evidence?
    Rahman, Motiur
    Dal Pan, Gerald
    Stein, Peter
    Levenson, Mark
    Kraus, Stefanie
    Chakravarty, Aloka
    Rivera, Donna R.
    Forshee, Richard
    Concato, John
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2024, 33 (01)
  • [50] Commentary - The development of real-world knowledge and reasoning in real-world contexts
    Ceci, SJ
    DEVELOPMENTAL REVIEW, 2002, 22 (02) : 323 - 330