Camera Obscurer: generative art for design inspiration

Dilpreet Singh; Nina Rajcic; Simon Colton; Jon McCormack

doi:10.1007/978-3-030-16667-0_4

Camera Obscurer: generative art for design inspiration

Dilpreet Singh, Nina Rajcic, Simon Colton, Jon McCormack

Department of Human Centred Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

3 Citations (Scopus)

Abstract

We investigate using generated decorative art as a source of inspiration for design tasks. Using a visual similarity search for image retrieval, the Camera Obscurer app enables rapid searching of tens of thousands of generated abstract images of various types. The seed for a visual similarity search is a given image, and the retrieved generated images share some visual similarity with the seed. Implemented in a hand-held device, the app empowers users to use photos of their surroundings to search through the archive of generated images and other image archives. Being abstract in nature, the retrieved images supplement the seed image rather than replace it, providing different visual stimuli including shapes, colours, textures and juxtapositions, in addition to affording their own interpretations. This approach can therefore be used to provide inspiration for a design task, with the abstract images suggesting new ideas that might give direction to a graphic design project. We describe a crowdsourcing experiment with the app to estimate user confidence in retrieved images, and we describe a pilot study where Camera Obscurer provided inspiration for a design task. These experiments have enabled us to describe future improvements, and to beginÂ to understand sources of visual inspiration for design tasks.

Original language	English
Title of host publication	Computational Intelligence in Music, Sound, Art and Design
Subtitle of host publication	8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings
Editors	Anikó Ekárt, Antonios Liapis, María Luz Castro Pena
Place of Publication	Cham Switzerland
Publisher	Springer
Pages	51-68
Number of pages	18
ISBN (Electronic)	9783030166670
ISBN (Print)	9783030166663
DOIs	https://doi.org/10.1007/978-3-030-16667-0_4
Publication status	Published - 2019
Event	International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2019 - Leipzig, Germany Duration: 24 Apr 2019 → 26 Apr 2019 Conference number: 8th http://www.evostar.org/2019/cfp_evomusart.php

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	11453
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2019
Abbreviated title	EvoMUSART 2019
Country	Germany
City	Leipzig
Period	24/04/19 → 26/04/19
Internet address	http://www.evostar.org/2019/cfp_evomusart.php

Access to Document

10.1007/978-3-030-16667-0_4

Link to publication in Scopus

Cite this

Singh, D., Rajcic, N., Colton, S., & McCormack, J. (2019). Camera Obscurer: generative art for design inspiration. In A. Ekárt, A. Liapis, & M. L. Castro Pena (Eds.), Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings (pp. 51-68). (Lecture Notes in Computer Science ; Vol. 11453). Springer. https://doi.org/10.1007/978-3-030-16667-0_4

Singh, Dilpreet ; Rajcic, Nina ; Colton, Simon ; McCormack, Jon. / Camera Obscurer : generative art for design inspiration. Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings. editor / Anikó Ekárt ; Antonios Liapis ; María Luz Castro Pena. Cham Switzerland : Springer, 2019. pp. 51-68 (Lecture Notes in Computer Science ).

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title = "Camera Obscurer: generative art for design inspiration",

abstract = "We investigate using generated decorative art as a source of inspiration for design tasks. Using a visual similarity search for image retrieval, the Camera Obscurer app enables rapid searching of tens of thousands of generated abstract images of various types. The seed for a visual similarity search is a given image, and the retrieved generated images share some visual similarity with the seed. Implemented in a hand-held device, the app empowers users to use photos of their surroundings to search through the archive of generated images and other image archives. Being abstract in nature, the retrieved images supplement the seed image rather than replace it, providing different visual stimuli including shapes, colours, textures and juxtapositions, in addition to affording their own interpretations. This approach can therefore be used to provide inspiration for a design task, with the abstract images suggesting new ideas that might give direction to a graphic design project. We describe a crowdsourcing experiment with the app to estimate user confidence in retrieved images, and we describe a pilot study where Camera Obscurer provided inspiration for a design task. These experiments have enabled us to describe future improvements, and to begin{\^A} to understand sources of visual inspiration for design tasks.",

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Singh, D, Rajcic, N, Colton, S & McCormack, J 2019, Camera Obscurer: generative art for design inspiration. in A Ekárt, A Liapis & ML Castro Pena (eds), Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings. Lecture Notes in Computer Science , vol. 11453, Springer, Cham Switzerland, pp. 51-68, International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design 2019, Leipzig, Germany, 24/04/19. https://doi.org/10.1007/978-3-030-16667-0_4

Camera Obscurer : generative art for design inspiration. / Singh, Dilpreet; Rajcic, Nina; Colton, Simon ; McCormack, Jon.

Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings. ed. / Anikó Ekárt; Antonios Liapis; María Luz Castro Pena. Cham Switzerland : Springer, 2019. p. 51-68 (Lecture Notes in Computer Science ; Vol. 11453).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AU - Singh, Dilpreet

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AU - McCormack, Jon

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N2 - We investigate using generated decorative art as a source of inspiration for design tasks. Using a visual similarity search for image retrieval, the Camera Obscurer app enables rapid searching of tens of thousands of generated abstract images of various types. The seed for a visual similarity search is a given image, and the retrieved generated images share some visual similarity with the seed. Implemented in a hand-held device, the app empowers users to use photos of their surroundings to search through the archive of generated images and other image archives. Being abstract in nature, the retrieved images supplement the seed image rather than replace it, providing different visual stimuli including shapes, colours, textures and juxtapositions, in addition to affording their own interpretations. This approach can therefore be used to provide inspiration for a design task, with the abstract images suggesting new ideas that might give direction to a graphic design project. We describe a crowdsourcing experiment with the app to estimate user confidence in retrieved images, and we describe a pilot study where Camera Obscurer provided inspiration for a design task. These experiments have enabled us to describe future improvements, and to beginÂ to understand sources of visual inspiration for design tasks.

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Singh D, Rajcic N, Colton S , McCormack J. Camera Obscurer: generative art for design inspiration. In Ekárt A, Liapis A, Castro Pena ML, editors, Computational Intelligence in Music, Sound, Art and Design: 8th International Conference, EvoMUSART 2019 Held as Part of EvoStar 2019 Leipzig, Germany, April 24–26, 2019 Proceedings. Cham Switzerland: Springer. 2019. p. 51-68. (Lecture Notes in Computer Science ). https://doi.org/10.1007/978-3-030-16667-0_4