Fusion of Perceptions in Architectural Design

被引:0
作者
Ciftcioglu, Ozer [1 ]
Bittermann, Michael S. [1 ]
机构
[1] Delft Univ Technol, NL-2600 AA Delft, Netherlands
来源
ECAADE 2013: COMPUTATION AND PERFORMANCE, VOL 2 | 2013年
关键词
Perception; vision modeling; architectural design; evolutionary search;
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A method for fusion of perceptions is presented. It is based on probabilistic treatment of perception, where perception quantifies the chance an unbiased observer sees an environmental object, and the associated probability can be interpreted as degree of awareness for the object. The approach uniquely accounts for the fact that final realization or remembrance of a scene in the brain may be absent or elusive, so that it is subject to probabilistic considerations. For objects that are to be perceived from multiple viewpoints, such as a sculpture in a museum, or a building in its urban context, the probabilistic approach uniquely defines the fusion of perceptions. This is accomplished by carrying out the probabilistic union of events. The computation is presented together with its geometric implications, which become rather intricate for multiple observers, whereas the computation is straight forward. The method is exemplified for two applications in architectural design at different scales, namely interior and urban design, indicating the generic nature as well as the large application potential of the method.
引用
收藏
页码:335 / 344
页数:10
相关论文
共 19 条
[1]  
Bhat M., 2011, Journal of Applied Ontology, V1, P1
[2]  
Bittermann Michael S., 2008, Journal of Design Research, V7, P35, DOI 10.1504/JDR.2008.018776
[3]  
Ciftcioglu O, 2006, ICIN CO 2006 3 INT C, P468
[4]   Towards computer-based perception by modeling visual perception:: A Probabilistic theory [J].
Ciftcioglu, Oe. ;
Bittermann, M. S. ;
Sariyildiz, I. S. .
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, :5152-+
[5]  
Foster John., 2000, Nature of Perception
[6]  
Gibson James J., 2015, ECOLOGICAL APPROACH, DOI DOI 10.4324/9781315740218
[7]  
Giese M, 2007, SPRINGER HDB ROBOTIC, P1481
[8]  
Goldberg DE, 2013, Genetic algorithms
[9]  
Knill D.C., 2008, PERCEPTION BAYESIAN, V1
[10]  
Mamassian P, 2008, PERCEPTION BAYESIAN, P239