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

PDF papers
References
id caadria2021_283
authors Sanatani, Rohit Priyadarshi, Chatterjee, Shamik Sambit and Manna, Ishita
year 2021
title Subject-specific Predictive Modelling for Urban Affect Analysis
source A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 387-396
doi https://doi.org/10.52842/conf.caadria.2021.2.387
summary Recent developments in crowd-sourced data collection and machine intelligence have facilitated data-driven analyses of the affective qualities of urban environments. While past studies have focused on the commonalities of affective experience across multiple subjects, this paper demonstrates an integrated framework for subject-specific affective data collection and predictive modelling. For demonstration, 10 field observers recorded their affective appraisals of various urban environments along the scales of Liveliness, Beauty, Comfort, Safety, Interestingness, Affluence, Stress and Familiarity. Data was collected through a mobile application that also recorded geo-location, date, time of day, a high resolution image of the users field of view, and a short audio clip of ambient sound. Computer vision algorithms were employed for extraction of six key urban features from the images - built score, paved score, auto score, sky score, nature score, and human score. For predictive modelling, K-Nearest Neighbour and Random Forest regression algorithms were trained on the subject-specific datasets of urban features and affective ratings. The algorithms were able to accurately assess the predicted affective qualities of new environments based on the specific individuals affective patterns.
keywords Urban Affect; Subjective Experience; Predictive Modelling; Affect Analysis
series CAADRIA
email
full text file.pdf (2,943,954 bytes)
references Content-type: text/plain
Details Citation Select
100%; open Aiello, LM, Schifanella, R, Quercia, D and Aletta, F (2016) Find in CUMINCAD Chatty maps: constructing sound maps of urban areas from social media data , Royal Society open science, 3(3), p. 150690

100%; open Aspinall, P, Mavros, P, Coyne, R and Roe, J (2015) Find in CUMINCAD The urban brain: analysing outdoor physical activity with mobile EEG , British journal of sports medicine, 49(4), pp. 272-276

100%; open Badrinarayanan, V, Kendall, A and Cipolla, R (2017) Find in CUMINCAD Segnet: A deep convolutional encoder-decoder architecture for image segmentation , IEEE transactions on pattern analysis and machine intelligence, 39(12), pp. 2481-2495

100%; open Chen, LC, Papandreou, G, Kokkinos, I, Murphy, K and Yuille, AL (2017) Find in CUMINCAD Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs , IEEE transactions on pattern analysis and machine intelligence, 40(4), pp. 834-848

100%; open Cordts, M, Omran, M, Ramos, S, Rehfeld, T, Enzweiler, M, Benenson, R, Franke, U, Roth, S and Schiele, B (2016) Find in CUMINCAD The cityscapes dataset for semantic urban scene understanding , Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 3213-3223

100%; open Dubey, A, Naik, N, Parikh, D, Raskar, R and Hidalgo, CA (2016) Find in CUMINCAD Deep learning the city: Quantifying urban perception at a global scale , European conference on computer vision, pp. 196-212

100%; open Huang, H and Gartner, G (2016) Find in CUMINCAD Using mobile crowdsourcing and geotagged social media data to study people's affective responses to environments , Capineri, C (eds), European Handbook of Crowdsourced Geographic Information, Ubiquity Press, pp. 385-399

100%; open Li, X, Zhang, C, Li, W, Ricard, R, Meng, Q and Zhang, W (2015) Find in CUMINCAD Assessing street-level urban greenery using Google Street View and a modified green view index , Urban Forestry & Urban Greening, 14(3), pp. 675-685

100%; open Naik, N, Philipoom, J, Raskar, R and Hidalgo, C (2014) Find in CUMINCAD Streetscore-predicting the perceived safety of one million streetscapes , Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 779-785

100%; open Ojha, VK, Griego, D, Kuliga, S, Bielik, M, Buš, P, Schaeben, C, Treyer, L, Standfest, M, Schneider, S and König, R (2019) Find in CUMINCAD Machine learning approaches to understand the influence of urban environments on human's physiological response , Information Sciences, 474, pp. 154-169

100%; open Salamon, J, Jacoby, C and Bello, JP (2014) Find in CUMINCAD A dataset and taxonomy for urban sound research , Proceedings of the 22nd ACM international conference on Multimedia, pp. 1041-1044

100%; open Sanatani, RP (2020) Find in CUMINCAD A machine-learning driven design assistance framework for the affective analysis of spatial enclosures , RE: Anthropocene, Design in the Age of Humans, Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2020), p. 741

100%; open Shen, Q, Zeng, W, Ye, Y, Arisona, SM, Schubiger, S, Burkhard, R and Qu, H (2017) Find in CUMINCAD StreetVizor: Visual exploration of human-scale urban forms based on street views , IEEE Transactions on Visualization and Computer Graphics, 24(1), pp. 1004-1013

100%; open Verma, D, Jana, A and Ramamritham, K (2018) Find in CUMINCAD Quantifying urban surroundings using deep learning techniques: a new proposal , Urban Science, 2(3), p. 78

100%; open Zeile, P, Resch, B, Dörrzapf, L, Exner, JP, Sagl, G, Summa, A and Sudmanns, M (2015) Find in CUMINCAD Urban Emotions-tools of integrating people's perception into urban planning , From vision to reality for vibrant cities and regions. Proceedings of 20th international conference on urban planning, regional development and information society, pp. 905-912

last changed 2022/06/07 07:56
pick and add to favorite papersHOMELOGIN (you are user _anon_685683 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002