Interactive color palette tools

Meier, Barbara J.; Spalter, Anne Morgan; Karelitz, David B.

doi:10.1109/mcg.2004.1297012

Cited by 76 publications

(42 citation statements)

References 6 publications

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“…One prominent class of applications is interfaces for color selection or palette design [1,3,12,19,28,37]. For example, PRAVDAColor [3] and ColorBrewer [12] suggest color palettes for encoding data in visualizations based on data types and/or cardinality.…”

Section: Tools For Color Designmentioning

confidence: 99%

“…For example, PRAVDAColor [3] and ColorBrewer [12] suggest color palettes for encoding data in visualizations based on data types and/or cardinality. Meier et al [19] apply theories of artistic color harmony [13,18] to assist interactive color selection. Cohen-Or et al [9] use these same theories to formulate automated color harmonization methods for image composition.…”

Section: Tools For Color Designmentioning

confidence: 99%

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Color naming models for color selection, image editing and palette design

Heer

Stone

2012

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

115

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Our ability to reliably name colors provides a link between visual perception and symbolic cognition. In this paper, we investigate how a statistical model of color naming can enable user interfaces to meaningfully mimic this link and support novel interactions. We present a method for constructing a probabilistic model of color naming from a large, unconstrained set of human color name judgments. We describe how the model can be used to map between colors and names and define metrics for color saliency (how reliably a color is named) and color name distance (the similarity between colors based on naming patterns). We then present a series of applications that demonstrate how color naming models can enhance graphical interfaces: a color dictionary & thesaurus, name-based pixel selection methods for image editing, and evaluation aids for color palette design.

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Section: Tools For Color Designmentioning

confidence: 99%

Section: Tools For Color Designmentioning

confidence: 99%

Color naming models for color selection, image editing and palette design

Heer

Stone

2012

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

115

View full text Add to dashboard Cite

show abstract

“…Meier et al [2004] and more recently Jalal et al [2015] study typical creation work ows, e.g. palette design, color replacement, and the generation of palettes similar to a given input palette.…”

Section: User-centered Pale E Explorationmentioning

confidence: 99%

“…Hue and harmonic templates coming from these fundamental works are now provided by all color manipulation tools as xed sets of rotations on the hue color wheel in the HSV space. While usual harmony templates ignore the HSV value components, Meier et al [2004] also propose non-planar harmony templates between colors. In addition to distances, Chang et al [2015] propose to preserve the luminance order between colors, as this property has a strong in uence on human perception.…”

Section: Color Constraintsmentioning

confidence: 99%

Constrained palette-space exploration

et al. 2017

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Color palettes are widely used by artists to define colors of artworks and explore color designs. In general, artists select the colors of a palette by following a set of rules, e.g. contrast or relative luminance. Existing interactive palette exploration tools explore palette spaces following limited constraints defined as geometric configurations in color space e.g. harmony rules on the color wheel. Palette search algorithms sample palettes from color relations learned from an input dataset, however they cannot provide interactive user edits and palette refinement. We introduce in this work a new versatile formulation enabling the creation of constraint-based interactive palette exploration systems. Our technical contribution is a graph-based palette representation, from which we define palette exploration as a minimization problem that can be solved efficiently and provide real-time feedback. Based on our formulation, we introduce two interactive palette exploration strategies: constrained palette exploration, and for the first time, constrained palette interpolation. We demonstrate the performances of our approach on various application cases and evaluate how it helps users finding trade-offs between concurrent constraints.

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“…We consider the color theme of an image to be a small set of colors, usually 3 to 7, that best represent that image. Being able to automatically extract good image-associated themes can facilitate applications such as color picking interfaces [18] and color mood transfer from one image to another [10,22]. Identifying the key colors in an image can also be useful in matching colors in a document or website around an image [20].…”

mentioning

confidence: 99%

Modeling how people extract color themes from images

Lin

Hanrahan

2013

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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Color choice plays an important role in works of graphic art and design. However, it can be difficult to choose a compelling set of colors, or color theme, from scratch. In this work, we present a method for extracting color themes from images using a regression model trained on themes created by people. We collect 1600 themes from Mechanical Turk as well as from artists. We find that themes extracted by Turk participants were similar to ones extracted by artists. In addition, people tended to select diverse colors and focus on colors in salient image regions. We show that our model can match human-extracted themes more closely compared to previous work. Themes extracted by our model were also rated higher as representing the image than previous approaches in a Mechanical Turk study.

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Interactive color palette tools

Cited by 76 publications

References 6 publications

Color naming models for color selection, image editing and palette design

Color naming models for color selection, image editing and palette design

Constrained palette-space exploration

Modeling how people extract color themes from images

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