CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id 2006_650
id 2006_650
authors Tourre, Vincent; Jean-Yves Martin and Gérard Hégron
year 2006
title Expression of luminous ambience intention in CAAD
source Communicating Space(s) [24th eCAADe Conference Proceedings / ISBN 0-9541183-5-9] Volos (Greece) 6-9 September 2006, pp. 650-655
summary This paper presents a research in progress dedicated to the development of a Computer Aided Architectural Design (CAAD) tool, which integrates design by ambience intention concept. A digital design by ambience intention framework is proposed, allowing intention expression of daylighting ambience through scene lighting properties. Lighting descriptors are introduced to represent theses properties, and combined to produce a lighting constraint set. These constraints are intended to be used in an inverse lighting model to compute geometrical raw solutions.
keywords Design by intention; Daylighting ambiance; Intention expression; CAAD tools; Inverse rendering
series eCAADe
email vincent.tourre@cerma.archi.fr
last changed 2006/08/16 16:54

_id ddss2008-14
id ddss2008-14
authors Zekri, Elyes; Gérard Hégron and Alain Legendre
year 2008
title Environmental Classification of Urban PedestrianWalkways
source H.J.P. Timmermans, B. de Vries (eds.) 2008, Design & Decision Support Systems in Architecture and Urban Planning, ISBN 978-90-6814-173-3, University of Technology Eindhoven, published on CD
summary This work is developed in the framework of urban design where we try to understand, to characterize then to qualify the environmental quality of urban open spaces along pedestrian walkways. So, we propose an analysis and a classification method applied to pedestrian walkways, taking into account their environmental characteristics. Analysis method is based on Discrete Wavelet Transform (DWT) in which we exploit the detailed version of the signal representing the evolution of a physical factor of environment along the walkway. This method leads to a segmentation of the signal. Then, a classification technique called Agglomerative Hierarchical Clustering (AHC) is performed to identify classes of walkways in terms of environmental features.
keywords Pedestrian walkways, physical factors of environment, wavelet, classification
series DDSS
last changed 2008/09/01 15:06

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