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Eye on the prize: using overt visual attention to drive fitness for interactive evolutionary computation

Published: 12 July 2008 Publication History

Abstract

Interactive Evolutionary Computation (IEC) has been applied to art and design problems where the fitness of an individual is at least partially subjective. Applications usually present a population from which the preferred individuals are selected before the usual evolutionary operations are performed to produce the next generation. Large population sizes and numbers of generations impose significant demands on the user. This paper proposes that selecting by means of eye movements could reduce user fatigue without sacrificing quality of fitness assessment. In the first experiment, an eye-tracker is used to capture fixations and confirm the reliability of such a measure of attention as a fitness driver for subjective evaluation such as aesthetic preference. In a second experiment, the robustness and efficiency of this technique is investigated for varying population sizes, presentation durations and levels of fitness sampling. The results and their consequences for future IEC applications are discussed.

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      cover image ACM Conferences
      GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation
      July 2008
      1814 pages
      ISBN:9781605581309
      DOI:10.1145/1389095
      • Conference Chair:
      • Conor Ryan,
      • Editor:
      • Maarten Keijzer
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 12 July 2008

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      Author Tags

      1. attention
      2. design/synthesis
      3. eye-movements
      4. fitness evaluation
      5. genetic algorithm
      6. interactive evolutionary computation
      7. visual perception

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      View all
      • (2024)3D Pop-Ups: Omnidirectional image visual saliency prediction based on crowdsourced eye-tracking data in VRDisplays10.1016/j.displa.2024.10274683(102746)Online publication date: Jul-2024
      • (2019)I see, you design: user interface intelligent design system with eye tracking and interactive genetic algorithmCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-019-00019-wOnline publication date: 4-Nov-2019
      • (2018)Design Preferred Aesthetic User Interface with Eye Movement and Electroencephalography DataProceedings of the 2018 ACM Companion International Conference on Interactive Surfaces and Spaces10.1145/3280295.3281748(39-45)Online publication date: 19-Nov-2018
      • (2018)Development of an Interactive Evolutionary Computation Catalog Interface with User Gaze InformationHCI International 2018 – Posters' Extended Abstracts10.1007/978-3-319-92270-6_17(121-128)Online publication date: 9-Jun-2018
      • (2018)Developing Female Clothing Coordination Generation System Using Eye Tracking InformationHuman-Computer Interaction. Interaction Technologies10.1007/978-3-319-91250-9_19(247-257)Online publication date: 1-Jun-2018
      • (2017)Application of an Eye Tracker Over Facility Layout Problem to Minimize User FatigueAdvances in Computational Intelligence10.1007/978-3-319-59153-7_13(145-156)Online publication date: 18-May-2017
      • (2017)Interactive Evolutionary Computation Using Multiple Users’ Gaze InformationHCI International 2017 – Posters' Extended Abstracts10.1007/978-3-319-58750-9_15(109-116)Online publication date: 13-May-2017
      • (2016)A Gaze-Driven Evolutionary Algorithm to Study Aesthetic Evaluation of Visual Symmetryi-Perception10.1177/20416695166374327:2(204166951663743)Online publication date: 22-Mar-2016
      • (2016)A Noninvasive Real-Time Solution for Driving Fatigue Detection Based on Left Prefrontal EEG and Eye BlinkBrain Informatics and Health10.1007/978-3-319-47103-7_32(325-335)Online publication date: 23-Sep-2016
      • (2015)Social Eye TrackingProceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing10.1145/2675133.2675249(454-463)Online publication date: 28-Feb-2015
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