Color-Blindness
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Rethinking Color Cameras
Rethinking Color Cameras Ayan Chakrabarti William T. Freeman Todd Zickler Harvard University Massachusetts Institute of Technology Harvard University Cambridge, MA Cambridge, MA Cambridge, MA [email protected] [email protected] [email protected] Abstract Digital color cameras make sub-sampled measurements of color at alternating pixel locations, and then “demo- saick” these measurements to create full color images by up-sampling. This allows traditional cameras with re- stricted processing hardware to produce color images from a single shot, but it requires blocking a majority of the in- cident light and is prone to aliasing artifacts. In this paper, we introduce a computational approach to color photogra- phy, where the sampling pattern and reconstruction process are co-designed to enhance sharpness and photographic speed. The pattern is made predominantly panchromatic, thus avoiding excessive loss of light and aliasing of high spatial-frequency intensity variations. Color is sampled at a very sparse set of locations and then propagated through- out the image with guidance from the un-aliased luminance channel. Experimental results show that this approach often leads to significant reductions in noise and aliasing arti- facts, especially in low-light conditions. Figure 1. A computational color camera. Top: Most digital color cameras use the Bayer pattern (or something like it) to sub-sample 1. Introduction color alternatingly; and then they demosaick these samples to create full-color images by up-sampling. Bottom: We propose The standard practice for one-shot digital color photog- an alternative that samples color very sparsely and is otherwise raphy is to include a color filter array in front of the sensor panchromatic. -
Spatial Filtering, Color Constancy, and the Color-Changing Dress Department of Psychology, American University, Erica L
Journal of Vision (2017) 17(3):7, 1–20 1 Spatial filtering, color constancy, and the color-changing dress Department of Psychology, American University, Erica L. Dixon Washington, DC, USA Department of Psychology and Department of Computer Arthur G. Shapiro Science, American University, Washington, DC, USA The color-changing dress is a 2015 Internet phenomenon divide among responders (as well as disagreement from in which the colors in a picture of a dress are reported as widely followed celebrity commentators) fueled a rapid blue-black by some observers and white-gold by others. spread of the photo across many online news outlets, The standard explanation is that observers make and the topic trended worldwide on Twitter under the different inferences about the lighting (is the dress in hashtag #theDress. The huge debate on the Internet shadow or bright yellow light?); based on these also sparked debate in the vision science community inferences, observers make a best guess about the about the implications of the stimulus with regard to reflectance of the dress. The assumption underlying this individual differences in color perception, which in turn explanation is that reflectance is the key to color led to a special issue of the Journal of Vision, for which constancy because reflectance alone remains invariant this article is written. under changes in lighting conditions. Here, we The predominant explanations in both scientific demonstrate an alternative type of invariance across journals (Gegenfurtner, Bloj, & Toscani, 2015; Lafer- illumination conditions: An object that appears to vary in Sousa, Hermann, & Conway, 2015; Winkler, Spill- color under blue, white, or yellow illumination does not change color in the high spatial frequency region. -
Color Constancy and Contextual Effects on Color Appearance
Chapter 6 Color Constancy and Contextual Effects on Color Appearance Maria Olkkonen and Vebjørn Ekroll Abstract Color is a useful cue to object properties such as object identity and state (e.g., edibility), and color information supports important communicative functions. Although the perceived color of objects is related to their physical surface properties, this relationship is not straightforward. The ambiguity in perceived color arises because the light entering the eyes contains information about both surface reflectance and prevailing illumination. The challenge of color constancy is to estimate surface reflectance from this mixed signal. In addition to illumination, the spatial context of an object may also affect its color appearance. In this chapter, we discuss how viewing context affects color percepts. We highlight some important results from previous research, and move on to discuss what could help us make further progress in the field. Some promising avenues for future research include using individual differences to help in theory development, and integrating more naturalistic scenes and tasks along with model comparison into color constancy and color appearance research. Keywords Color perception • Color constancy • Color appearance • Context • Psychophysics • Individual differences 6.1 Introduction Color is a useful cue to object properties such as object identity and state (e.g., edibility), and color information supports important communicative functions [1]. Although the perceived color of objects is related to their physical surface properties, M. Olkkonen, M.A. (Psych), Dr. rer. nat. (*) Department of Psychology, Science Laboratories, Durham University, South Road, Durham DH1 3LE, UK Institute of Behavioural Sciences, University of Helsinki, Siltavuorenpenger 1A, 00014 Helsinki, Finland e-mail: [email protected]; maria.olkkonen@helsinki.fi V. -
Color Dictionaries and Corpora
Encyclopedia of Color Science and Technology DOI 10.1007/978-3-642-27851-8_54-1 # Springer Science+Business Media New York 2015 Color Dictionaries and Corpora Angela M. Brown* College of Optometry, Department of Optometry, Ohio State University, Columbus, OH, USA Definition In the study of linguistics, a corpus is a data set of naturally occurring language (speech or writing) that can be used to generate or test linguistic hypotheses. The study of color naming worldwide has been carried out using three types of data sets: (1) corpora of empirical color-naming data collected from native speakers of many languages; (2) scholarly data sets where the color terms are obtained from dictionaries, wordlists, and other secondary sources; and (3) philological data sets based on analysis of ancient texts. History of Color Name Corpora and Scholarly Data Sets In the middle of the nineteenth century, color-name data sets were primarily from philological analyses of ancient texts [1, 2]. Analyses of living languages soon followed, based on the reports of European missionaries and colonialists [3, 4]. In the twentieth century, influential data sets were elicited directly from native speakers [5], finally culminating in full-fledged empirical corpora of color terms elicited using physical color samples, reported by Paul Kay and his collaborators [6, 7]. Subsequently, scholarly data sets were published based on analyses of secondary sources [8, 9]. These data sets have been used to test specific hypotheses about the causes of variation in color naming across languages. From the study of corpora and scholarly data sets, it has been known for over 150 years that languages differ in the number of color terms in common use. -
The Neural Control of Fast Vs. Slow Vergence Eye Movements
European Journal of Neuroscience European Journal of Neuroscience, Vol. 33, pp. 2147–2154, 2011 doi:10.1111/j.1460-9568.2011.07692.x The neural control of fast vs. slow vergence eye movements Kathleen E. Cullen and Marion R. Van Horn Department of Physiology, Aerospace Medical Research Unit, McGill University, Montreal, PQ, Canada Keywords: binocular, burst neuron, conjugate, extraocular, monocular, saccade Abstract When looking between targets located in three-dimensional space, information about relative depth is sent from the visual cortex to the motor control centers in the brainstem, which are responsible for generating appropriate motor commands to move the eyes. Surprisingly, how the neurons in the brainstem use the depth information supplied by the visual cortex to precisely aim each eye on a visual target remains highly controversial. This review will consider the results of recent studies that have focused on determining how individual neurons contribute to realigning gaze when we look between objects located at different depths. In particular, the results of new experiments provide compelling evidence that the majority of saccadic neurons dynamically encode the movement of an individual eye, and show that the time-varying discharge of the saccadic neuron population encodes the drive required to account for vergence facilitation during disconjugate saccades. Notably, these results suggest that an additional input (i.e. from a separate vergence subsystem) is not required to shape the activity of motoneurons during disconjugate saccades. Furthermore, whereas motoneurons drive both fast and slow vergence movements, saccadic neurons discharge only during fast vergence movements, emphasizing the existence of distinct premotor pathways for controlling fast vs. -
Our Senses & Information Processing
Our senses What we see Light entering our eyes Question: How Tall does a mirror have to be to see your body from head to toe? Prediction A plane mirror is affixed to the wall. What do you think the minimum length of the mirror must be for you to see your entire body from head to toe (just as tall, ¾ as tall, ½ as tall etc…)? At what height does a mirror of this length need to be mounted to allow you to see your entire body from head to toe? Why is this? Procedure Materials: Plane mirror mounted to the wall, meter stick, dry erase marker. Note: While you’re waiting your turn for the mirror, skip to page 5 and start on one of the activities listed on pages 5, 6 or 7. 1. Choose your two most extreme group members, the tallest and the shortest. A. Have the shortest member, known as the object, stand in front of the plane mirror. Another group member will mark on the mirror with a dry erase marker where the object sees the top of their head. Then mark where the object sees their feet. Cover the unused areas of the mirror to verify that they are not needed for the object to see themselves from head to foot. B. Now have the object test to see how distance from the mirror affects the necessary size of mirror. The object should stand very close and very far from the mirror the entire time checking to see how the original head and feet marks align with their head and feet respectively. -
Fast Fourier Color Constancy
Fast Fourier Color Constancy Jonathan T. Barron Yun-Ta Tsai [email protected] [email protected] Abstract based techniques in computer vision, both problems reduce to just estimating the “best” illuminant from an image, and We present Fast Fourier Color Constancy (FFCC), a the question of whether that illuminant is objectively true color constancy algorithm which solves illuminant esti- or subjectively attractive is just a matter of the data used mation by reducing it to a spatial localization task on a during training. torus. By operating in the frequency domain, FFCC pro- Despite their accuracy, modern learning-based color duces lower error rates than the previous state-of-the-art by constancy algorithms are not immediately suitable as prac- 13 − 20% while being 250 − 3000× faster. This unconven- tical white balance algorithms, as practical white balance tional approach introduces challenges regarding aliasing, has several requirements besides accuracy: directional statistics, and preconditioning, which we ad- Speed - An algorithm running in a camera’s viewfinder dress. By producing a complete posterior distribution over must run at 30 FPS on mobile hardware. But a camera’s illuminants instead of a single illuminant estimate, FFCC compute budget is precious: demosaicing, face detection, enables better training techniques, an effective temporal auto exposure, etc, must also run simultaneously and in real smoothing technique, and richer methods for error analy- time. Spending more than a small fraction (say, 5 − 10%) sis. Our implementation of FFCC runs at ∼ 700 frames per of a camera’s compute budget on white balance is impracti- second on a mobile device, allowing it to be used as an ac- cal, suggesting that our speed requirement is closer to 1 − 5 curate, real-time, temporally-coherent automatic white bal- milliseconds per frame. -
Vergence Eye Movements Redefined: the Neural Control of Fast Versus Slow Vergence
Vergence eye movements redefined: The neural control of fast versus slow vergence Marion R. Van Horn Aerospace Medical Research Unit Department of Physiology McGill University Montreal, Quebec, Canada August 2010 A thesis submitted to the faculty of Graduate Studies and Research in partial fulfilment of the degree of Doctorate in Philosophy Copyright © Marion Van Horn 2010 TABLE OF CONTENTS ABSTRACT…………………………..…………………………..………………... xiii RÉSUMÉ…………………………..…………………………..…………………… xv ACKNOWLEDGEMENTS…………………………..………………………… ..xviii CONTRIBUTIONS OF AUTHORS…………………………..………………….. xx LIST OF ABBREVIATIONS…………………………………..……………….. xxii CHAPTER 1: GENERAL INTRODUCTION & LITERATURE REVIEW 1.1 Overview and conceptual framework………...……………………………… 1 1.2 The extraocular eye muscles and their innervations…………….…………… 4 1.3 Classification of eye movements………………….…………….…………… 8 1.4 The neural control of disconjugate saccades: Hering versus Helmoholtz... 11 1.4.1 Evidence supporting Hering’s Law …………………………….... 11 1.5 The premotor circuitry of conjugate saccades ………………………….... 14 1.5.1 Saccadic burst neurons…………….…………………………….... 15 1.5.2 Omnipause neurons………………..…………………………….... 16 1.5.3 Oculomotor integration ………………………………………….... 17 1.6 The premotor circuitry of saccade-free vergence ……………………….... 19 1.7 Evidence against “Hering’s Law” ……………………………………….... 20 1.8 Research Goals ……………………………….………………………….... 22 CHAPTER 2: DYNAMIC CHARACTERIZATION OF OCULOMOTONEURONS DURING CONJUGATE AND DISCONJUGATE EYE MOVEMENTS 2.1 ABSTRACT ………………………………………………………………. 25 2.2 INTRODUCTION -
The Basic Colour Terms of Finnish1
Mari Uusküla The Basic Colour Terms of Finnish1 Abstract This article describes a study of Finnish colour terms the aim of which was to establish an inventory of basic colour terms, and to compare the results to the list of basic terms suggested by Mauno Koski (1983). Basic colour term in this study is understood as Brent Berlin and Paul Kay defined it in 1969. The data for the study was collected using the field method of Ian Davies and Greville Corbett (1994). Sixty-eight native speakers of Finnish, aged 10 to 75, performed two tasks: a colour-term list task (name as many colours as you know) and a colour naming task (where the subjects were asked to name 65 representative colour tiles). The list task was complemented by the cognitive salience index designed by Sutrop (2001). An analysis of the results shows that there are 10 basic colour terms in Finnish—punainen ‘red,’ sininen ‘blue,’ vihreä ‘green,’ keltainen ‘yellow,’ musta ‘black,’ valkoinen ‘white,’ oranssi ‘orange,’ ruskea ‘brown,’ harmaa ‘grey,’ and vaaleanpunainen ‘pink’. These results contrast with Mauno Koski’s claim that there are only 8 basic colour terms in Finnish. However, both studies agree that Finnish does not possess a basic colour term for purple. 1. Introduction Basic colour terms are a relatively well studied area of vocabulary and studies on them cover many languages of the world. Research on colour terms became particularly intense after the publication of Berlin and Kay’s (1969) inspiring and much debated monograph. Berlin and Kay argued that basic colour terms in all languages are drawn from a universal inventory of just 11 colour categories (see Figure 1). -
Berlin and Kay Theory
Encyclopedia of Color Science and Technology DOI 10.1007/978-3-642-27851-8_62-2 # Springer Science+Business Media New York 2013 Berlin and Kay Theory C.L. Hardin* Department of Philosophy, Syracuse University, Syracuse, NY, USA Definition The Berlin-Kay theory of basic color terms maintains that the world’s languages share all or part of a common stock of color concepts and that terms for these concepts evolve in a constrained order. Basic Color Terms In 1969 Brent Berlin and Paul Kay advanced a theory of cross-cultural color concepts centered on the notion of a basic color term [1]. A basic color term (BCT) is a color word that is applicable to a wide class of objects (unlike blonde), is monolexemic (unlike light blue), and is reliably used by most native speakers (unlike chartreuse). The languages of modern industrial societies have thousands of color words, but only a very slender stock of basic color terms. English has 11: red, yellow, green, blue, black, white, gray, orange, brown, pink, and purple. Slavic languages have 12, with separate basic terms for light blue and dark blue. In unwritten and tribal languages the number of BCTs can be substantially smaller, perhaps as few as two or three, with denotations that span much larger regions of color space than the BCT denotations of major modern languages. Furthermore, reconstructions of the earlier vocabularies of modern languages show that they gain BCTs over time. These typically begin as terms referring to a narrow range of objects and properties, many of them noncolor properties, such as succulence, and gradually take on a more general and abstract meaning, with a pure color sense. -
Color Naming Experiment in Mongolian Language
International Journal of Applied Linguistics & English Literature ISSN 2200-3592 (Print), ISSN 2200-3452 (Online) Vol. 4 No. 6; November 2015 Flourishing Creativity & Literacy Australian International Academic Centre, Australia Color Naming Experiment in Mongolian Language Nandin-Erdene Osorjamaa (Corresponding author) The National University of Mongolia, Orkhon school, Department of Translation Studies, Mongolia E-mail: [email protected], [email protected] Nansalmaa Nyamjav School of Science, Faculty of Humanities, Department of European Studies The National University of Mongolia, Mongolia E-mail: [email protected] Received: 20-03- 2015 Accepted: 21-06- 2015 Advance Access Published: August 2015 Published: 01-11- 2015 doi:10.7575/aiac.ijalel.v.4n.6p.58 URL: http://dx.doi.org/10.7575/aiac.ijalel.v.4n.6p.58 Abstract There are numerous researches on color terms and names in many languages. In Mongolian language there are few doctoral theses on color naming. Cross cultural studies of color naming have demonstrated Semantic relevance in French and Mongolian color name Gerlee Sh. (2000); Comparisons of color naming across English and Mongolian Uranchimeg B. (2004); Semantic comparison between Russian and Mongolian idioms Enhdelger O. (1996); across symbolism Dulam S. (2007) and few others. Also a few articles on color naming by some Mongolian scholars are Tsevel, Ya. (1947), Baldan, L. (1979), Bazarragchaa, M. (1997) and others. Color naming studies are not sufficiently studied in Modern Mongolian. Our research is considered to be the first intended research on color naming in Modern Mongolian, because it is one part of Ph.D dissertation on color naming. There are two color naming categories in Mongolian, basic color terms and non- basic color terms. -
Kay (?) Color Naming Across Languages
2. Color Naming Across Languages Paul Kay, Brent Berlin, Luisa Maffi and William Merrifield 1. Introduction: Prior cross-linguistic research on color naming This chapter summarizes some of the research on cross-linguistic color categorization and naming that has addressed issues raised in Basic Color Terms: Their Universality and Evolution (Berlin and Kay 1969, hereafter B&K). It then advances some speculations regarding future developments—especially regarding the analysis, now in progress, of the data of the World Color Survey (hereafter WCS). In the latter respect the chapter serves as something of a progress report on the current state of analysis of the WCS data, as well as a promissory note on the full analysis to come. B&K proposed two general hypotheses about basic color terms and the categories they name: (1) there is a restricted universal inventory of such categories; (2) a language adds basic color terms in a constrained order, interpreted as an evolutionary sequence. These two hypotheses have been substantially confirmed by subsequent research.1 There have been changes in the more detailed formulation of the hypotheses, as well as additional empirical findings and theoretical interpretations since 1969. Rosch’s experimental work on Dani color (Heider 1972a, 1972b), supplemented by personal communications from anthropologists and linguists, showed that two-term systems contain, not terms for dark and light shades regardless of hue—as B&K had inferred—but rather one term covering white, red and yellow and one term covering black, green and blue, that is, a category of white plus ‘warm’ colors versus one of black plus ‘cool’ colors.