Structural Beauty: A Structure-based Approach to Quantifying the Beauty
of an Image
- URL: http://arxiv.org/abs/2104.11100v1
- Date: Fri, 16 Apr 2021 08:48:34 GMT
- Title: Structural Beauty: A Structure-based Approach to Quantifying the Beauty
of an Image
- Authors: Bin Jiang and Chris de Rijke
- Abstract summary: Christopher Alexander has long discovered that beauty or coherence highly correlates to the number of subsymmetries or substructures.
This paper develops an approach for computing the structural beauty or life of an image based on the number of automatically derived substructures.
- Score: 7.032744060924398
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: To say that beauty is in the eye of the beholder means that beauty is largely
subjective so varies from person to person. While the subjectivity view is
commonly held, there is also an objectivity view that seeks to measure beauty
or aesthetics in some quantitative manners. Christopher Alexander has long
discovered that beauty or coherence highly correlates to the number of
subsymmetries or substructures and demonstrated that there is a shared notion
of beauty - structural beauty - among people and even different peoples,
regardless of their faiths, cultures, and ethnicities. This notion of
structural beauty arises directly out of living structure or wholeness, a
physical and mathematical structure that underlies all space and matter. Based
on the concept of living structure, this paper develops an approach for
computing the structural beauty or life of an image (L) based on the number of
automatically derived substructures (S) and their inherent hierarchy (H). To
verify this approach, we conducted a series of case studies applied to eight
pairs of images including Leonardo da Vinci's Mona Lisa and Jackson Pollock's
Blue Poles. We discovered among others that Blue Poles is more structurally
beautiful than the Mona Lisa, and traditional buildings are in general more
structurally beautiful than their modernist counterparts. This finding implies
that goodness of things or images is largely a matter of fact rather than an
opinion or personal preference as conventionally conceived. The research on
structural beauty has deep implications on many disciplines, where beauty or
aesthetics is a major concern such as image understanding and computer vision,
architecture and urban design, humanities and arts, neurophysiology, and
psychology.
Keywords: Life; wholeness; figural goodness; head/tail breaks; computer
vision
Related papers
- Representing Beauty: Towards a Participatory but Objective Latent Aesthetics [51.56484100374058]
We show how aesthetic content produces more similar and aligned representations between models.<n>We argue that human perceptual and creative acts play a central role in shaping these latent spaces of deep learning systems.<n>Our findings suggest that human-machine co-creation is not merely possible, but foundational.
arXiv Detail & Related papers (2025-10-03T10:09:37Z) - Disc-Cover Complexity Trends in Music Illustrations from Sinatra to Swift [51.70874799858211]
We examine the visual complexity of album covers spanning 75 years and 11 popular musical genres.<n>Our analysis reveals a broad shift toward minimalism across most genres, with notable exceptions.<n>At the same time, we observe growing variance over time, with many covers continuing to display high levels of abstraction and intricacy.
arXiv Detail & Related papers (2025-10-01T15:01:25Z) - The Photographer Eye: Teaching Multimodal Large Language Models to Understand Image Aesthetics like Photographers [82.99499130882576]
Photographer and curator, Szarkowski insightfully revealed one of the notable gaps between general and aesthetic visual understanding.<n>We present a novel dataset, PhotoCritique, derived from extensive discussions among professional photographers and enthusiasts.<n>We also propose a novel model, PhotoEye, featuring a languageguided multi-view vision fusion mechanism to understand image aesthetics from multiple perspectives.
arXiv Detail & Related papers (2025-09-23T02:59:41Z) - Aesthetics Without Semantics [3.644950723229025]
We create a database of images with minimal semantic content and devise a method to generate images on the ugly side of aesthetic valuations.<n>We show how augmenting an image set biased towards beautiful images with ugly images can modify, or even invert, an observed relationship between image features and aesthetics valuation.
arXiv Detail & Related papers (2025-05-08T15:22:11Z) - Beautimeter: Harnessing GPT for Assessing Architectural and Urban Beauty based on the 15 Properties of Living Structure [4.959120401369489]
Beautimeter is a new tool powered by generative pre-trained transformer (GPT) technology.
Alexander identified 15 fundamental properties, such as levels of scale and thick boundaries, that characterize living structure.
By integrating GPT's advanced natural language processing capabilities, Beautimeter assesses the extent to which a structure embodies these 15 properties.
arXiv Detail & Related papers (2024-11-28T12:14:24Z) - A Complexity-Based Theory of Compositionality [53.025566128892066]
In AI, compositional representations can enable a powerful form of out-of-distribution generalization.
Here, we propose a formal definition of compositionality that accounts for and extends our intuitions about compositionality.
The definition is conceptually simple, quantitative, grounded in algorithmic information theory, and applicable to any representation.
arXiv Detail & Related papers (2024-10-18T18:37:27Z) - Impressions: Understanding Visual Semiotics and Aesthetic Impact [66.40617566253404]
We present Impressions, a novel dataset through which to investigate the semiotics of images.
We show that existing multimodal image captioning and conditional generation models struggle to simulate plausible human responses to images.
This dataset significantly improves their ability to model impressions and aesthetic evaluations of images through fine-tuning and few-shot adaptation.
arXiv Detail & Related papers (2023-10-27T04:30:18Z) - Recursive Segmentation Living Image: An eXplainable AI (XAI) Approach
for Computing Structural Beauty of Images or the Livingness of Space [4.959120401369489]
This study introduces the concept of "structural beauty" as an objective computational approach for evaluating the aesthetic appeal of images.
The application of our method to the Scenic or Not dataset, a repository of subjective scenic ratings, demonstrates a high degree of consistency with subjective ratings in the 0-6 score range.
Our method not only provides computational results but also offers transparency and interpretability, positioning it as a novel avenue in the realm of Explainable AI (XAI)
arXiv Detail & Related papers (2023-10-16T07:37:20Z) - HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion [114.15397904945185]
We propose a unified framework, HyperHuman, that generates in-the-wild human images of high realism and diverse layouts.
Our model enforces the joint learning of image appearance, spatial relationship, and geometry in a unified network.
Our framework yields the state-of-the-art performance, generating hyper-realistic human images under diverse scenarios.
arXiv Detail & Related papers (2023-10-12T17:59:34Z) - Text-to-Image Generation for Abstract Concepts [76.32278151607763]
We propose a framework of Text-to-Image generation for Abstract Concepts (TIAC)
The abstract concept is clarified into a clear intent with a detailed definition to avoid ambiguity.
The concept-dependent form is retrieved from an LLM-extracted form pattern set.
arXiv Detail & Related papers (2023-09-26T02:22:39Z) - Intrinsic Physical Concepts Discovery with Object-Centric Predictive
Models [86.25460882547581]
We introduce the PHYsical Concepts Inference NEtwork (PHYCINE), a system that infers physical concepts in different abstract levels without supervision.
We show that object representations containing the discovered physical concepts variables could help achieve better performance in causal reasoning tasks.
arXiv Detail & Related papers (2023-03-03T11:52:21Z) - Living Images: A Recursive Approach to Computing the Structural Beauty
of Images or the Livingness of Space [5.566946186234262]
We argue that the more substructures, the more living or more structurally beautiful, and the higher hierarchy of the substructures, the more living or more structurally beautiful.
We show that the number of substructures of an image is far lower (3 percent on average) than the number of pixels and the centroids of the substructures can effectively capture the skeleton or saliency of the image.
arXiv Detail & Related papers (2023-01-04T20:27:32Z) - PTR: A Benchmark for Part-based Conceptual, Relational, and Physical
Reasoning [135.2892665079159]
We introduce a new large-scale diagnostic visual reasoning dataset named PTR.
PTR contains around 70k RGBD synthetic images with ground truth object and part level annotations.
We examine several state-of-the-art visual reasoning models on this dataset and observe that they still make many surprising mistakes.
arXiv Detail & Related papers (2021-12-09T18:59:34Z) - A Hypothesis for the Aesthetic Appreciation in Neural Networks [17.58003267114874]
This paper proposes a hypothesis for the aesthetic appreciation that aesthetic images make a neural network strengthen salient concepts and discard inessential concepts.
In experiments, we find that the revised images are more aesthetic than the original ones to some extent.
arXiv Detail & Related papers (2021-07-31T06:19:00Z) - Formalising Concepts as Grounded Abstractions [68.24080871981869]
This report shows how representation learning can be used to induce concepts from raw data.
The main technical goal of this report is to show how techniques from representation learning can be married with a lattice-theoretic formulation of conceptual spaces.
arXiv Detail & Related papers (2021-01-13T15:22:01Z) - The Platonic solids and fundamental tests of quantum mechanics [0.0]
The Platonic solids have transcended traditional boundaries and entered the stage in a range of disciplines.
Motivated by mathematical beauty and a rich history, we consider the Platonic solids in the context of modern quantum mechanics.
arXiv Detail & Related papers (2020-01-01T10:46:15Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.