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 acadia06_483
authors Yan, Wei
year 2006
title Integrating Video Tracking and Virtual Reality in Environmental Behavior Study
source Synthetic Landscapes [Proceedings of the 25th Annual Conference of the Association for Computer-Aided Design in Architecture] pp. 483-488
doi https://doi.org/10.52842/conf.acadia.2006.483
summary One of the essential considerations in architectural design is how people use the built environments. Adequate study of environmental behavior can reveal significant information about that use. This research suggests applying new computing technologies to enhance environmental behavior study, in terms of effectiveness and efficiency. Specifically, this project will develop an integrated system of automatic video tracking and video-quality virtual reality. The integrated system will provide designers and behavioral scientists with substantial statistical measurements of end user behavior patterns. Furthermore it will enable them to walk through the virtual reality of the environments and interactively observe details of the behaviors from various viewpoints. Thus, this project can help obtain behavior data in different levels of details, and in a structured and planned way that can facilitate analysis of the data with maximum automation. The major significance of this project is an introduction of a rigorous new methodology into environmental behavior study to enhance first-person observation with state-of-the-art computing technologies. This research will be a novel application of virtual reality in environmental behavior study. We expect that it will fundamentally advance the methods behavioral scientists use to study human environmental behavior, and the ways architects evaluate architectural design in terms of human behavior.
series ACADIA
email
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100%; open Yan, W. and Forsyth, D. (2005) Find in CUMINCAD Learning the Behavior of Users in a Public Space through Video Tracking , Proceedings of IEEE Workshop on Applications of Computer Vision (WACV 05)

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