Measuring streetscape complexity based on the statistics of local contrast and spatial frequency.
Streetscapes are basic urban elements which play a major role in the livability of a city. The visual complexity of streetscapes is known to influence how people behave in such built spaces. However, how and which characteristics of a visual scene influence our perception of complexity have yet to be fully understood. This study proposes a method to evaluate the complexity perceived in streetscapes based on the statistics of local contrast and spatial frequency. Here, 74 streetscape images from four cities, including daytime and nighttime scenes, were ranked for complexity by 40 participants. Image processing was then used to locally segment contrast and spatial frequency in the streetscapes. The statistics of these characteristics were extracted and later combined to form a single objective measure. The direct use of statistics revealed structural or morphological patterns in streetscapes related to the perception of complexity. Furthermore, in comparison to conventional measures of visual complexity, the proposed objective measure exhibits a higher correlation with the opinion of the participants. Also, the performance of this method is more robust regarding different time scenarios.
Department of Media Science, Graduate School of Information Science, Nagoya University, Nagoya-shi, Aichi-ken, Japan.
André
A
Cavalcante
Department of Architecture, Nagoya Institute of Technology, Nagoya-shi, Aichi-ken, Japan.
Ahmed
A
Mansouri
Department of Architecture, Nagoya Institute of Technology, Nagoya-shi, Aichi-ken, Japan.
Lemya
L
Kacha
Department of Electrical Engineering and Electronics, Universidade Federal do Maranhão, São Luís, Maranhão, Brazil.
Allan Kardec
AK
Barros
Department of Information Systems, School of Informatics, Daido University, Nagoya-shi, Aichi-ken, Japan.
Yoshinori
Y
Takeuchi
Department of Architecture, Nagoya Institute of Technology, Nagoya-shi, Aichi-ken, Japan.
Naoji
N
Matsumoto
Department of Media Science, Graduate School of Information Science, Nagoya University, Nagoya-shi, Aichi-ken, Japan.
Noboru
N
Ohnishi
D000462:Algeria; D000465:Algorithms; D002947:Cities; D015350:Contrast Sensitivity; D004779:Environment Design / Q000592:standards* / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000145:classification / Q000592:standards; D007564:Japan; D008297:Male; D010364:Pattern Recognition, Visual; D010781:Photography / Q000145:classification / Q000592:standards; D013997:Time Factors