Will It Blend? Studying Color Mixing Perception Paulo Duarte Esperanc¸a Garcia Thesis to obtain the Master of Science Degree in Information Systems and Computer Engineering Supervisors: Prof. Dr. Daniel Jorge Viegas Gonc¸alves Prof. Dra. Sandra Pereira Gama Examination Committee Chairperson: Prof. Dr. Antonio´ Manuel Ferreira Rito da Silva Supervisor: Prof. Dr. Daniel Jorge Viegas Gonc¸alves Member of the Committee: Prof. Dr. Manuel Joao˜ Caneira Monteiro da Fonseca November 2016 Acknowledgments First, I want to thank my advisor Professor Daniel Gonc¸alves for his excellent guidance, for always having the availability to teach, help and clarify, for his enormous knowledge and expertise, and for al- ways believing in the best result possible of this Master Thesis. Then, I also want to thank my co-advisor Sandra Gama, for her more-than-valuable inputs on Information Visualization and for opening the path for this dissertation and others to come! Additionally, I would like to thank everyone which somehow contributed for this thesis to happen: everyone who participated either online, or on the laboratory sessions, specially those who did it so willingly, without looking at the rewards. Without them, there would be no validity is this thesis. I must express my very profound gratitude to my family, particularly my mother Ondina and brother Diogo, for providing me with unfailing support and continuous encouragement throughout my years of study and through the process of researching and writing this thesis. This accomplishment would not have been possible without them. Thank you! Finally, to my girlfriend Margarida, my beloved partner, my shelter and support, for all the sleepless nights, sweat and tears throughout the last seven years. Thank you for always believing in me, for being who you are, and for all the little things. i Abstract Using color to convey information is not a recent rule: its usage is further associated to standards, statis- tics and computer science. However, color is a subjective aspect of human perception, as it is strongly influenced by cultural background, childhood learning and possible existent color vision deficiencies. Color is also frequently used to convey information, while associating it to data variables: commonly, one color is attributed to only variable but, would it be interesting to attribute one color to two data vari- ables simultaneously? Over the last years, previous investigation has not come to an agreement about to which extent can color blending techniques be used, in an effective way, to convey information. We intended to study if the users can detect the blending-basis when the result of a given color mixture is given, and vice-versa. We have found that CMYK is the color model that best resembles users’ expec- tations, while the orange color-blending results is the one which generates shorter distances between the reference colors and the ones indicated. Whilst, the CIE-L*C*h* Model is the one which is farther apart from the users’ mental model of color. We have also detected that there is a mild indicator that there exists a difference between the responses from Female and Male users. All the data collected was developed through a user study, supported by an online user studies platform called BlendMe!. As product of this Master thesis, we collected a set relevant implications of using color blending tech- niques, besides providing a set of questions apart from the ones answered by the us, which remain unanswered and could turn out as an interesting source of future work. Keywords: colors, blending, InfoVis, perception, calibration, bins iii Resumo A utilizac¸ao˜ de cores para transmitir informac¸ao˜ nao˜ e´ pratica´ recente: esta´ fortemente associada a standards e nomenclaturas de acordo com cores, apresentac¸ao˜ de estat´ısticas e contagens de dados, para alem´ da cienciaˆ da computac¸ao.˜ Contudo, a cor e´ um aspecto consideravelmente subjectivo da percepc¸ao˜ humana do meio que nos envolve, ja´ que e´ fortemente influenciado pelas ra´ızes culturais, pelas aprendizagens obtidas na infanciaˆ e, tambem,´ por poss´ıveis deficienciasˆ que existam no sistema visual humano. A cor e´ tambem´ frequentemente utilizada para transmitir informac¸ao,˜ ao associa-la a variaveis´ de dados: commumente, uma cor e´ atribuida a apenas uma variavel´ mas, nao˜ seria inte- ressante atribuir uma mesma cor a duas variaveis´ simultaneamente? Ao longo dos ultimos´ anos, a investigac¸ao˜ realizada revelou-se inconclusiva em relac¸ao˜ a` utilizac¸ao˜ de tecnicas´ de mistura de cor. O objectivo da nossa investigac¸ao˜ e´ estudar se os utilizadores conseguem detectar as bases de uma mistura de cor quando lhe e´ fornecido o resultado da mesma, e vice-versa. Concluimos, entre outros temas, que o modelo CMYK e´ o que melhor retrata as expectativas de mistura do utilizador, enquanto que o laranja e´ a cor que origina distanciasˆ mais curtas entre as cores de referencia,ˆ e as indicadas pelos utilizadores; por outro lado, o modelo CIE-L*C*h* e´ o que mais se distancia do modelo mental de cor dos utilizadores. Detectamos´ tambem´ existir uma ligeira diferenc¸a nos resultados indicados pe- los utilizadores femininos e masculinos. Todos os resultados foram recolhidos com base num estudo realizado com utilizadores, suportado por uma plataforma de estudos de utilizador online denominada BlendMe!. Como resultados desta Tese de Mestrado, retiramos´ algumas implicac¸oes˜ relevantes sobre o uso de tecnicas´ de mistura de cor, na area´ de Visualizac¸ao˜ de Informac¸ao.˜ Palavras-chave: cores, misturas, InfoVis, percepc¸ao,˜ calibrac¸ao,˜ bins v Contents List of Tables ix List of Figures xiii 1 Introduction 1 1.1 Contributions . .3 1.2 Dissertation Outline . .3 2 Background 5 2.1 Theoretical Background . .5 2.1.1 Color Perception . .5 Color Philosophy . .5 2.1.2 The Human Eye . .6 Theories of Color Vision . .8 Visual Deficiency . .8 Mental Models and Codes . .9 2.1.3 Color Models and Spaces . 10 Colorimetry . 10 Color Fundamental Concepts . 11 Defining Color Models . 12 Defining Color Spaces . 14 Color Calibration . 16 Color Scales . 17 2.2 Related Work . 18 2.2.1 Color Blending Research and Techniques . 19 Data Visualization . 19 Perception of Relative Amounts of Color . 20 Other Research . 20 2.2.2 Color Blending Alternatives . 22 Color Weaving . 22 Hue-Preserving Color Blending . 23 2.3 Discussion . 24 3 BlendMe! - The User Study 27 3.1 Objectives . 27 3.2 Designing the BlendMe! ..................................... 28 3.2.1 User Profiling Phase . 30 3.2.2 Testing Calibration Phase . 31 vii 3.2.3 Testing Color Vision Deficiencies Phase . 32 3.2.4 Core Test Phase . 33 3.3 Evaluation Criteria . 35 4 Analyzing Color Mixing Perception 37 4.1 Protocol . 37 4.1.1 Laboratory Environment . 37 4.1.2 Online Environment . 38 4.1.3 Broadcasting the User Study . 38 4.2 Data Cleaning . 39 4.3 Data Processing . 40 4.3.1 Data Preparation . 41 4.3.2 Color Bins Comparison . 42 4.3.3 Outputs Generated . 44 4.4 Results . 44 4.4.1 User Profile . 44 4.4.2 Color Models . 45 Analyzing Questions . 46 Analyzing Color Models . 56 Color Blending Expectation . 63 4.4.3 Color Mixtures and Color Naming . 68 Primary Colors . 68 Color Blending Effort . 73 4.4.4 Demographic Results . 75 Age Groups . 75 Gender Groups . 76 Color Vision Deficient Users Group . 78 4.5 Discussion . 80 4.5.1 Guidelines for the usage of Color Blending . 82 4.5.2 Calibration Resiliency . 83 4.5.3 Implications for InfoVis . 84 5 Conclusion 87 5.1 Limitations . 88 5.2 Future Work . 88 Bibliography 89 A User Study Protocol 91 A.1 Motivation . 91 A.2 User Profiling Phase . 91 A.3 Testing Calibration Phase . 91 A.4 Testing Color Vision Deficiences Phase . 92 A.5 Core Test Phase . 92 B Processing Data 93 C Color Bins 101 C.1 Color Map . 101 viii List of Tables 3.1 Two types of questions asked about Color Blendings. 29 4.1 Excerpt of Clean ”Results”Table . ..