Generative Models for Experimentation and Knowledge of Perspective Principles

被引:0
|
作者
Fasolo, Marco [1 ]
Valenti, Graziano Mario [1 ]
Camagni, Flavia [1 ]
机构
[1] Sapienza Univ Roma, Dept Hist Representat & Restorat Architecture, Piazza Borghese 9, I-00186 Rome, Italy
关键词
Perspective; Interactive generative parametric models; Descriptive geometry; E-learning; Educational methodology;
D O I
10.1007/978-3-030-20216-3_25
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The research investigates experimental digital models, used to enhance the educational methodology, concerning the fundamentals of graphic representation, especially in the general sense of perspective models. In this experimentation, we examine the high communicative efficacy of a generative parametric interactive models, constructed on the basis of visual nodal programming, which: on one hand makes it possible to explain in graphic form the hierarchical and temporal relation of geometrical operations and projective on which the representation is based; on the other hand it allows to experiment the parametric dynamic models, in order to appropriate the perceptual changes that arise from the projective variations that can be established between the geometrical entities present in the models. A possibility, this dynamic interaction, which has not yet been sufficiently experienced and that deserves attention and research.
引用
收藏
页码:264 / 275
页数:12
相关论文
共 50 条
  • [1] EXPERIMENTATION AND KNOWLEDGE - A PRAGMATIC PERSPECTIVE
    MASON, RO
    KNOWLEDGE-CREATION DIFFUSION UTILIZATION, 1988, 10 (01): : 3 - 24
  • [2] Generative Models: An Interdisciplinary Perspective
    Sankaran, Kris
    Holmes, Susan P.
    ANNUAL REVIEW OF STATISTICS AND ITS APPLICATION, 2023, 10 : 325 - 352
  • [3] Generative Diffusion Models: Principles and Applications
    Tanaka, Akinori
    JOURNAL OF THE PHYSICAL SOCIETY OF JAPAN, 2025, 94 (03)
  • [4] Generative Models for Relief Perspective Architectures
    Baglioni, Leonardo
    Fallavollita, Federico
    NEXUS NETWORK JOURNAL, 2021, 23 (04) : 879 - 898
  • [5] Generative Models for Relief Perspective Architectures
    Leonardo Baglioni
    Federico Fallavollita
    Nexus Network Journal, 2021, 23 : 879 - 898
  • [6] Group invariance principles for causal generative models
    Besserve, Michel
    Shajarisales, Naji
    Schoelkopf, Bernhard
    Janzing, Dominik
    INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS, VOL 84, 2018, 84
  • [7] A Knowledge Management Perspective of Generative Artificial Intelligence
    Alavi, Maryam
    Leidner, Dorothy E.
    Mousavi, Reza
    JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2024, 25 (01): : 1 - 12
  • [8] Explicit Disentanglement of Appearance and Perspective in Generative Models
    Detlefsen, Nicki S.
    Hauberg, Soren
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32
  • [9] Deep Generative Models with Learnable Knowledge Constraints
    Hu, Zhiting
    Yang, Zichao
    Salakhutdinov, Ruslan
    Liang, Xiaodan
    Qin, Lianhui
    Dong, Haoye
    Xing, Eric P.
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 2018, 31
  • [10] Generative Models from the perspective of Continual Learning
    Lesort, Timothee
    Caselles-Dupre, Hugo
    Garcia-Ortiz, Michael
    Stoian, Andrei
    Filliat, David
    2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,