Computational Aesthetic Evaluation: Past and Future

Galanter, Philip

doi:10.1007/978-3-642-31727-9_10

Cited by 65 publications

(45 citation statements)

References 82 publications

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“…The experiments of this work lie at the crossroad between Computational Aesthetics and Personality Computing (see [12] and [16] for an extensive surveys). To the best of our knowledge, no other works have addressed the problem of mapping favorite pictures into personality traits.…”

Section: Previous Workmentioning

confidence: 99%

The Pictures We Like Are Our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits

Segalin

Perina

Cristani

et al. 2017

IEEE Trans. Affective Comput.

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Abstract-Flickr allows its users to tag the pictures they like as "favorite". As a result, many users of the popular photo-sharing platform produce galleries of favorite pictures. This article proposes new approaches, based on Computational Aesthetics, capable to infer the personality traits of Flickr users from the galleries above. In particular, the approaches map low-level features extracted from the pictures into numerical scores corresponding to the Big-Five Traits, both self-assessed and attributed. The experiments were performed over 60,000 pictures tagged as favorite by 300 users (the PsychoFlickr Corpus). The results show that it is possible to predict beyond chance both self-assessed and attributed traits. In line with the state-of-theart of Personality Computing, these latter are predicted with higher effectiveness (correlation up to 0.68 between actual and predicted traits).

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Section: Previous Workmentioning

confidence: 99%

The Pictures We Like Are Our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits

Segalin

Perina

Cristani

et al. 2017

IEEE Trans. Affective Comput.

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“…One motivation for selecting this metric over some of the more recent methods from the field of computational aesthetics [25,26] is that harmony does not expect patterns to be derived from images. Other metrics frequently assume they are being used for image assessment and therefore rely on the calculation of quantities, such as compression ratios, or statistics related to image properties, such as colour, which make them difficult to apply to non-image patterns.…”

Section: Harmony Pattern Metricmentioning

confidence: 99%

Aesthetic Local Search of Wind Farm Layouts

Mayo

Daoud

2017

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Abstract:The visual impact of wind farm layouts has seen little consideration in the literature on the wind farm layout optimisation problem to date. Most existing algorithms focus on optimising layouts for power or the cost of energy alone. In this paper, we consider the geometry of wind farm layouts and whether it is possible to bi-optimise a layout for both energy efficiency and the degree of visual impact that the layout exhibits. We develop a novel optimisation approach for solving the problem which measures mathematically the degree of visual impact of a layout. The approach draws inspiration from the field of architecture. To evaluate our ideas, we demonstrate them on three benchmark problems for the wind farm layout optimisation problem in conjunction with two recently-published stochastic local search algorithms. Optimal patterned layouts are shown to be very close in terms of energy efficiency to optimal non-patterned layouts.

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“…as exhibited in, say, mateselection). Galanter [19] suggests that perhaps the 'computational equivalent' of a bird or an insect (e.g. in evaluating mate selection) is all that is required for [computational] aesthetic evaluation:…”

Section: On Art Freedom and Creativitymentioning

confidence: 99%

Weak and Strong Computational Creativity

al-Rifaie

Bishop

2014

Atlantis Thinking Machines

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In the spirit of Searle's definition of weak and strong artificial intelligence, this paper presents a discussion on weak computational creativity in swarm intelligence systems. It addresses the concepts of freedom and constraint and their impact on the creativity of the underlying systems. An analogy is drawn on mapping these two 'prerequisites' of creativity onto the two well-known phases of exploration and exploitation in swarm intelligence algorithms, followed by the visualisation of the behaviour of the swarms whose performance are evaluated in the context of arguments presented. The paper also discusses that the strong computational creativity is presented in ways emphasising that genuine creativity implies 'genuine understanding' and other cognitive states, along with autonomy -asserting that without 'Strong Embodiment', computational systems are not genuinely autonomous.

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Computational Aesthetic Evaluation: Past and Future

Cited by 65 publications

References 82 publications

The Pictures We Like Are Our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits

The Pictures We Like Are Our Image: Continuous Mapping of Favorite Pictures into Self-Assessed and Attributed Personality Traits

Aesthetic Local Search of Wind Farm Layouts

Weak and Strong Computational Creativity

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