Cumincad : CUMINCAD Papers : Search Results

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	caadria2018_103
id	caadria2018_103
authors	Liu, Chang, Zhang, Xu and Nagakura, Takehiko
year	2018
title	PanoFrame: A Lightweight Panoramic Video Editing Tool for Storytelling with Spatial Content
doi	https://doi.org/10.52842/conf.caadria.2018.2.567
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 567-576
summary	As low-cost panoramic cameras become prevalent among non-professional consumers, an easy-to-use panoramic video editing tool is required for emerging storytellers. This paper proposes a lightweight online panoramic video editing tool for storytelling and explores a method of interpreting the same spatial content from different perspectives with panoramic videos. We conducted three experiments using different groups of participants to test how people create, understand, and interact with a panoramic video story in the proposed tool. The results reveal that this tool enables storytellers to work collaboratively and create multiple narratives from a panoramic video, and the generated panoramic video narratives are also more attractive to audiences than the raw video. This tool has the potential to be an ever-growing crowdsourcing community with a database of multiple narratives and creates opportunities for designers to record, learn about and present architectural and urban space from multiple perspectives.
keywords	Storytelling; panoramic video; spatial content; multiple perspective narrative; crowdsourcing
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2018_164
id	ecaade2018_164
authors	Chang, Mei-Chih, Buš, Peter, Tartar, Ayça, Chirkin, Artem and Schmitt, Gerhard
year	2018
title	Big-Data Informed Citizen Participatory Urban Identity Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 669-678
summary	The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective.
keywords	Urban identity; unsupervised machine learning; Principal Component Analysis (PCA); citizen participated design; space syntax
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ijac201816304
id	ijac201816304
authors	Miao, Yufan; Reinhard Koenig, Katja Knecht, Kateryna Konieva, Peter Buš and Mei-Chih Chang
year	2018
title	Computational urban design prototyping: Interactive planning synthesis methods—a case study in Cape Town
source	International Journal of Architectural Computing vol. 16 - no. 3, 212-226
summary	This article is motivated by the fact that in Cape Town, South Africa, approximately 7.5 million people live in informal settlements and focuses on potential upgrading strategies for such sites. To this end, we developed a computational method for rapid urban design prototyping. The corresponding planning tool generates urban layouts including street network, blocks, parcels and buildings based on an urban designer’s specific requirements. It can be used to scale and replicate a developed urban planning concept to fit different sites. To facilitate the layout generation process computationally, we developed a new data structure to represent street networks, land parcellation, and the relationship between the two. We also introduced a nested parcellation strategy to reduce the number of irregular shapes generated due to algorithmic limitations. Network analysis methods are applied to control the distribution of buildings in the communities so that preferred neighborhood relationships can be considered in the design process. Finally, we demonstrate how to compare designs based on various urban analysis measures and discuss the limitations that arise when we apply our method in practice, especially when dealing with more complex urban design scenarios.
keywords	Procedural modeling, spatial synthesis, generative design, urban planning
series	journal
email
last changed	2019/08/07 14:03

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