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computational aesthetics of photos quality assessment based on improved artificial neural network combined with an autoencoder technique

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NEUROCOMPUTING 2016年 188卷 50-62页

作者： Tan, Yunlan Zhou, Yimin Li, Guangyao Huang, Anmin Jinggangshan Univ Sch Elect & Informat Engn Jian Jiangxi Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 200092 Peoples R China

Photograph aesthetical evaluation has been widely investigated in these decades. For fine-granularity aesthetic quality prediction, a novel aesthetics classifier based on improved artificial neural network combined with an Autoencoder technique is presented. First, we download large consumer photographic images from a well-known online photograph portal. Then, we extract 56 features normalized to 0-1 and train the networks with photographs of high and low ratings to test the quality of photos. Experimental results show that the accuracy of classification is above 86.67%, which is better than all state-of-the-art methods. Meanwhile, it is observed from experiments that the extracted features are consistent with the humans' visual perception systems. (C) 2015 Elsevier B.V. All rights reserved.

关键词： computational aesthetics Quality assessment Artificial neural network Autoencoder High aesthetics Low aesthetics

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computational aesthetics and applications

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Visual Computing for Industry,Biomedicine,and Art 2018年第1期1卷 50-68页

作者： Yihang Bo Jinhui Yu Kang Zhang Department of Fine Art Beijing Film AcademyBeijing 100088China The State Key Lab.of CAD&CG Zhejiang UniversityHangzhou 310058China Department of Computer Science The University of Texas at DallasRichardsonTX 75080USA

computational aesthetics,which bridges science and art,is emerging as a new interdisciplinary *** paper concentrates on two main aspects of computational aesthetics:aesthetic measurement and quantification,generative art,and then proposes a design generation *** aesthetic measurement and quantification,we review different types of features used in measurement,the currently used evaluation methods,and their *** generative art,we focus on both fractal art and abstract paintings modeled on well-known artists’*** general,computational aesthetics exploits computational methods for aesthetic *** other words,it enables computer to appraise beauty and ugliness and also automatically generate aesthetic *** aesthetics has been widely applied to many areas,such as photography,fine art,Chinese hand-writing,web design,graphic design,and industrial *** finally propose a design generation methodology,utilizing techniques from both aesthetic measurements and generative art.

关键词： computational aesthetics Aesthetic measurement Generative art Fractal art Abstract painting

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Applying computational aesthetics to a Video Game Application Using Machine Learning

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 2016年第4期36卷 23-33页

作者： Erdem, Ali Naci Halici, Ugur Middle East Tech Univ Ankara Turkey Middle East Tech Univ Dept Elect & Elect Engn Ankara Turkey

The authors have developed a novel approach to evaluating the aesthetic quality of the camera direction in video game scenes rendered in real time while the game is being played. Their goal was to improve the visual aesthetic quality of computer-generated images using a computational aesthetics approach via a regression machine learning model. Considering the challenges and limitations involved, the proposed approach yielded promising prediction performance. The results show that near-real-time aesthetic analysis and visual improvement is possible using a virtual camera director.

关键词： Cameras Computer Games Image Processing Learning Artificial Intelligence Regression Analysis computational aesthetics Video Game Camera Direction Visual Aesthetic Quality Computer Generated Images Regression Machine Learning Cameras Image Color Analysis Feature Extraction Games Training Predictive Models Correlation Coefficient Computer Graphics Quality Assessment Machine Learning computational aesthetics Regression Machine Learning Aesthetic Analysis Video Games

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Salient-Centeredness and Saliency Size in computational aesthetics

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ACM TRANSACTIONS ON APPLIED PERCEPTION 2023年第2期20卷 1-23页

作者： Hoh, Weng Khuan Zhang, Fang-Lue Dodgson, Neil A. Victoria Univ Wellington Wellington 6011 New Zealand

We investigate the optimal aesthetic location and size of a single dominant salient region in a photographic image. Existing algorithms for photographic composition do not take full account of the spatial positioning or sizes of these salient regions. We present a set of experiments to assess aesthetic preferences, inspired by theories of centeredness, principal lines, and Rule-of-Thirds. Our experimental results show a clear preference for the salient region to be centered in the image and that there is a preferred size of non-salient border around this salient region. We thus propose a novel image cropping mechanism for images containing a single salient region to achieve the best aesthetic balance. Our results show that the Rule-of-Thirds guideline is not generally valid but also allow us to hypothesize in which situations it is useful and in which it is inappropriate.

关键词： computational aesthetics image aesthetics image saliency visual balance salient-centeredness Rule-of-Thirds photographic composition

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The Performance Analysis of Low-Resolution Paintings for computational aesthetics 13th

The Performance Analysis of Low-Resolution Paintings for Com...

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13th International Symposium on Smart Graphics (SG)

作者： Zhu, Juan Pu, Yuan Yuan Xu, Dan Qian, Wen Hua Wang, Li Qing Yunnan Univ Sch Informat Sci & Engn Kunming 650091 Yunnan Peoples R China Yunnan Univ Digital Media Technol Key Lab Univ Yunnan Kunming 650091 Yunnan Peoples R China

ISBN: (纸本)9783319538389;9783319538372

In the study of computational aesthetics, we always use high-resolution paintings to analyze painting style, but actually the paintings we obtain mostly are low-resolution. In this paper, the contrast experiments based on sparse coding are carried out between high and low resolution paintings. Different features are extracted in frequency domain and Gabor domain from the basis function of sparse coding (SC). Then the normalized mutual information (NMI) is figured out to analyze the effect of different features for painting style. At last, the features with better performance are used to classify the paintings' style. The results of experiments show that, to a certain extent, the features extracted from low-resolution paintings still have the ability to characterize the painting style, among which the Gabor energy has the best effect in the painting style analysis.

关键词： computational aesthetics Image resolution Sparse coding Feature extraction Normalized mutual information

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Exploration of the Relationship between UIDL and Interface computational aesthetics 13

Exploration of the Relationship between UIDL and Interface C...

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13th ACM International Conference on Interactive Surfaces and Spaces (ISS)

作者： Wen, Quan Ren, Xiangshi Wang, Chen Sun, Xiaoying Jilin Univ 5988 People St Changchun 130022 Jilin Peoples R China Kochi Univ Technol Kami Japan

ISBN: (纸本)9781450360104

This paper explores the relationship between user interface description language (UIDL) and interface computational aesthetics. First, a framework was designed to integrate aesthetic factors into the whole process of UIDL. Then, two issues about cross-device and aesthetic template are discussed, and the integration feasibility is proved. We expect our framework to facilitate in the popularization and application of computational aesthetics.

关键词： UIDL computational aesthetics

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Exploring the Influence of Object, Subject, and Context on Aesthetic Evaluation through computational aesthetics and Neuroaesthetics

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APPLIED SCIENCES-BASEL 2024年第16期14卷 7384页

作者： Lin, Fangfu Xu, Wanni Li, Yan Song, Wu Huaqiao Univ Coll Mech Engn & Automat Xiamen 361021 Peoples R China Fuzhou Univ Xiamen Acad Arts & Design Xiamen 361021 Peoples R China

Background: In recent years, computational aesthetics and neuroaesthetics have provided novel insights into understanding beauty. Building upon the findings of traditional aesthetics, this study aims to combine these two research methods to explore an interdisciplinary approach to studying aesthetics. Method: Abstract artworks were used as experimental materials. Based on traditional aesthetics and in combination, features of composition, tone, and texture were selected. computational aesthetic methods were then employed to correspond these features to physical quantities: blank space, gray histogram, Gray Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP), and Gabor filters. An electroencephalogram (EEG) experiment was carried out, in which participants conducted aesthetic evaluations of the experimental materials in different contexts (genuine, fake), and their EEG data were recorded to analyze the impact of various feature classes in the aesthetic evaluation process. Finally, a Support Vector Machines (SVMs) was utilized to model the feature data, Event-Related Potentials (ERPs), context data, and subjective aesthetic evaluation data. Result: Behavioral data revealed higher aesthetic ratings in the genuine context. ERP data indicated that genuine contexts elicited more negative deflections in the prefrontal lobes between 200 and 1000 ms. Class II compositions demonstrated more positive deflections in the parietal lobes at 50-120 ms, while Class I tones evoked more positive amplitudes in the occipital lobes at 200-300 ms. Gabor features showed significant variations in the parieto-occipital area at an early stage. Class II LBP elicited a prefrontal negative wave with a larger amplitude. The results of the SVM models indicated that the model incorporating aesthetic subject and context data (ACC = 0.76866) outperforms the model using only parameters of the aesthetic object (ACC = 0.68657). Conclusion: A positive context tends to provide participants with

关键词： aesthetics computational aesthetics neuroaesthetics EEG ERP SVM

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computational models and experimental investigations of effects of balance and symmetry on the aesthetics of text-overlaid images

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INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES 2010年第1-2期68卷 41-56页

作者： Lai, Chien-Yin Chen, Pai-Hsun Shih, Sheng-Wen Liu, Yili Hong, Jen-Shin Natl Chi Nan Univ Dept Comp Sci & Informat Engn Puli 545 Nantou Hsien Taiwan Nan Kai Univ Technol Dept Comp Sci & Informat Engn Tsao Tun 542 Nantou Hsien Taiwan Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA

This article describes computational models based on principles of visual weights to compute the symmetry and balance of text-overlaid images. Two experiments were conducted to investigate the effects of symmetry and balance on the aesthetic appeal of text-overlaid images. In the first experiment, five color photos were used to compose a set of test images overlaid with a paragraph of Chinese texts as the stimuli. Contrastly, the second experiment applied monochrome photos to compute the stimuli. The positions of the text overlay were determined by varying the balance and symmetry in order to validate computational aesthetic quantification algorithms with subjective ratings. The stimuli were rated by 20 subjects in each experiment using the ratio-scale magnitude estimation method against a benchmark image for each photo. Results from both experiments show that subjects are adept at judging symmetry and balance in both the horizontal and vertical directions. Subjects are also adept at judging radial symmetry about the center point of an image. The experiments also established a relationship between a higher averaged visual balance and the aesthetic appeal of text-overlaid images. Symmetry in either direction, however, did not result in any proportional relations to the aesthetic appeal. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： computational aesthetics Interface design Compositional attributes

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A computational framework for aesthetic preferences in architecture using computer vision and artificial neural networks

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INTERNATIONAL JOURNAL OF ARCHITECTURAL COMPUTING 2025年第1期23卷 174-192页

作者： Sardenberg, Victor Guatelli, Igor Becker, Mirco Leibniz Univ Hannover Hannover Germany Univ Presbiteriana Mackenzie Digital Methods Architecture Sao Paulo Brazil

This paper introduces a computational aesthetics framework utilizing computer vision (CV) and artificial neural networks (ANN) to predict the aesthetic preferences of groups of people for architecture. It relies on part-to-whole theories from aesthetics and cognitive psychology. A survey of a group of people on preferences of images is held to record an average hedonic response (AHR). CV algorithms MSER and SAM recognize parts in images. Birkhoff's aesthetic measure formula is adapted by employing the number of parts and their connections. These quantities are used as input layers of an ANN, and the AHR is the target output. The ANN evaluates images to output a predicted hedonic response (PHR), which is tested as a criterion in parametric design space navigation and in mapping the latent space of GANs. We conclude that such a framework is a heuristic method for better understanding the design and latent spaces and exploring designs.

关键词： Artificial neural networks computational aesthetics computer vision design space navigation empirical aesthetics hedonic response heuristics latent space map quantitative aesthetics

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computational and Experimental Approaches to Visual aesthetics

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FRONTIERS IN computational NEUROSCIENCE 2017年 11卷 102页

作者： Brachmann, Anselm Redies, Christoph Univ Jena Jena Univ Hosp Inst Anat Sch MedExpt Aesthet Grp Jena Germany

aesthetics has been the subject of long-standing debates by philosophers and psychologists alike. In psychology, it is generally agreed that aesthetic experience results from an interaction between perception, cognition, and emotion. By experimental means, this triad has been studied in the field of experimental aesthetics, which aims to gain a better understanding of how aesthetic experience relates to fundamental principles of human visual perception and brain processes. Recently, researchers in computer vision have also gained interest in the topic, giving rise to the field of computational aesthetics. With computing hardware and methodology developing at a high pace, the modeling of perceptually relevant aspect of aesthetic stimuli has a huge potential. In this review, we present an overview of recent developments in computational aesthetics and how they relate to experimental studies. In the first part, we cover topics such as the prediction of ratings, style and artist identification as well as computational methods in art history, such as the detection of influences among artists or forgeries. We also describe currently used computational algorithms, such as classifiers and deep neural networks. In the second part, we summarize results from the field of experimental aesthetics and cover several isolated image properties that are believed to have a effect on the aesthetic appeal of visual stimuli. Their relation to each other and to findings from computational aesthetics are discussed. Moreover, we compare the strategies in the two fields of research and suggest that both fields would greatly profit from a joined research effort. We hope to encourage researchers from both disciplines to work more closely together in order to understand visual aesthetics from an integrated point of view.

关键词： computational aesthetics experimental aesthetics visual preference art history artist identification style identification image features statistical image properties

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