scholarly journals Color appearance of familiar objects: Effects of object shape, texture, and illumination changes

2008 ◽  
Vol 8 (5) ◽  
pp. 13 ◽  
Author(s):  
Maria Olkkonen ◽  
Thorsten Hansen ◽  
Karl R. Gegenfurtner
Keyword(s):  
Color Appearance ◽  
Object Shape ◽  
Illumination Changes ◽  
Familiar Objects

Perception of speed, distance, and TTC of familiar objects.

2017 ◽  
Vol 10 (3) ◽  
pp. 261-272 ◽  
Author(s):  
Andrés Martín ◽  
Agustín P. Décima ◽  
Jose F. Barraza
Keyword(s):  
Familiar Objects

How are object shape axes defined? Evidence from mirror-image confusions.

2019 ◽  
Vol 45 (1) ◽  
pp. 111-124 ◽  
Author(s):  
Thitaporn Chaisilprungraung ◽  
Joseph German ◽  
Michael McCloskey
Keyword(s):  
Mirror Image ◽  
Object Shape

A mathematical model of real-world object shape predicts human perceptual judgments

2018 ◽  
Author(s):  
Caterina Magri ◽  
Andrew Marantan ◽  
L Mahadevan ◽  
Talia Konkle
Keyword(s):  
Mathematical Model ◽  
Real World ◽  
Object Shape ◽  
Perceptual Judgments

Change of color appearance due to extremely high light level: corresponding colors under 100 and 3000 cd/m2

2019 ◽  
Vol 2019 (1) ◽  
pp. 320-325 ◽  
Author(s):  
Wenyu Bao ◽  
Minchen Wei
Keyword(s):  
Light Level ◽  
Limited Range ◽  
High Light ◽  
Color Preference ◽  
Color Appearance ◽  
Appearance Model ◽  
Color Matching ◽  
Light Levels ◽  
Appearance Models ◽  
Psychophysical Study

Great efforts have been made to develop color appearance models to predict color appearance of stimuli under various viewing conditions. CIECAM02, the most widely used color appearance model, and many other color appearance models were all developed based on corresponding color datasets, including LUTCHI data. Though the effect of adapting light level on color appearance, which is known as "Hunt Effect", is well known, most of the corresponding color datasets were collected within a limited range of light levels (i.e., below 700 cd/m2), which was much lower than that under daylight. A recent study investigating color preference of an artwork under various light levels from 20 to 15000 lx suggested that the existing color appearance models may not accurately characterize the color appearance of stimuli under extremely high light levels, based on the assumption that the same preference judgements were due to the same color appearance. This article reports a psychophysical study, which was designed to directly collect corresponding colors under two light levels— 100 and 3000 cd/m2 (i.e., ≈ 314 and 9420 lx). Human observers completed haploscopic color matching for four color stimuli (i.e., red, green, blue, and yellow) under the two light levels at 2700 or 6500 K. Though the Hunt Effect was supported by the results, CIECAM02 was found to have large errors under the extremely high light levels, especially when the CCT was low.

Real-world environment affects the color appearance of virtual stimuli produced by augmented reality

2019 ◽  
Vol 2019 (1) ◽  
pp. 237-242
Author(s):  
Siyuan Chen ◽  
Minchen Wei
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Mixed Reality ◽  
Rapid Development ◽  
Light Level ◽  
Color Appearance ◽  
Chromatic Adaptation ◽  
Lighting Condition ◽  
The Real ◽  
World Environment

Color appearance models have been extensively studied for characterizing and predicting the perceived color appearance of physical color stimuli under different viewing conditions. These stimuli are either surface colors reflecting illumination or self-luminous emitting radiations. With the rapid development of augmented reality (AR) and mixed reality (MR), it is critically important to understand how the color appearance of the objects that are produced by AR and MR are perceived, especially when these objects are overlaid on the real world. In this study, nine lighting conditions, with different correlated color temperature (CCT) levels and light levels, were created in a real-world environment. Under each lighting condition, human observers adjusted the color appearance of a virtual stimulus, which was overlaid on a real-world luminous environment, until it appeared the whitest. It was found that the CCT and light level of the real-world environment significantly affected the color appearance of the white stimulus, especially when the light level was high. Moreover, a lower degree of chromatic adaptation was found for viewing the virtual stimulus that was overlaid on the real world.

Color Constancy

2017 ◽  
Author(s):  
Joshua Gert
Keyword(s):  
Visual Representation ◽  
Color Constancy ◽  
Color Appearance ◽  
Fine Grained ◽  
Hybrid View

This chapter presents an account of color constancy that explains a well-known division in the data from color-constancy experiments: So-called “paper matches” exhibit a much higher level of constancy than so-called “hue-saturation matches.” It argues that the visual representation of objective color is the representation of something associated with a function from viewing circumstances to color appearances. Thus, a relatively robust constancy in the representation of objective color is perfectly consistent with a relatively less robust level of constancy in color appearance. The account also endorses Hilbert’s idea that we can represent the color of the illumination on a surface as well as the color of the surface itself. Finally, the chapter addresses an objection to the hybrid view that notes our capacity to make very fine-grained distinctions between the objective colors of surfaces.

scholarly journals Spinal vertebrae localization and analysis on disproportionality in curvature using radiography—a comprehensive review

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Joddat Fatima ◽  
Muhammad Usman Akram ◽  
Amina Jameel ◽  
Adeel Muzaffar Syed
Keyword(s):  
Spinal Cord ◽  
Template Matching ◽  
Human Anatomy ◽  
Comprehensive Overview ◽  
Low Contrast ◽  
Active Shape Models ◽  
Harris Corner ◽  
Illumination Changes ◽  
The Central Nervous System ◽  
The Brain

AbstractIn human anatomy, the central nervous system (CNS) acts as a significant processing hub. CNS is clinically divided into two major parts: the brain and the spinal cord. The spinal cord assists the overall communication network of the human anatomy through the brain. The mobility of body and the structure of the whole skeleton is also balanced with the help of the spinal bone, along with reflex control. According to the Global Burden of Disease 2010, worldwide, back pain issues are the leading cause of disability. The clinical specialists in the field estimate almost 80% of the population with experience of back issues. The segmentation of the vertebrae is considered a difficult procedure through imaging. The problem has been catered by different researchers using diverse hand-crafted features like Harris corner, template matching, active shape models, and Hough transform. Existing methods do not handle the illumination changes and shape-based variations. The low-contrast and unclear view of the vertebrae also makes it difficult to get good results. In recent times, convolutional nnural Network (CNN) has taken the research to the next level, producing high-accuracy results. Different architectures of CNN such as UNet, FCN, and ResNet have been used for segmentation and deformity analysis. The aim of this review article is to give a comprehensive overview of how different authors in different times have addressed these issues and proposed different mythologies for the localization and analysis of curvature deformity of the vertebrae in the spinal cord.

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