Capturing what human eyes perceive: A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks

Wenjie Zhen, Lin Yang, Mei Po Kwan, Zejun Zuo, Bo Wan, Shunping Zhou, Shengwen Li, Yaqin Ye, Haoyue Qian, Xiaofang Pan

Research output: Contribution to journalArticle

Abstract

Visual hierarchy is an important notion in urban imagery research. As the skeletons of cities, urban streets attract more attention from urban residents and street network hierarchies are important references for urban planning and urban studies. However, due to the characteristic of over-regularization, it is often difficult for humans to differentiate visual salience for grid-like street networks, resulting in the hierarchies of grid-like streets yielded by existing methods being prone to cause visual cognitive confusion. Therefore, in this study, we proposed a novel model to quantify the extent to which a street attracts human visual attention through emulating the visual attention mechanism that can capture the focus of relatively significant elements at different levels of perception. Using the natural street (also known as the stroke) as the sensor unit, the comprehensive visual salience (CVS) index combining the geometric competitive factors of natural streets at the local scale and psychological competitive factors of natural streets at the global scale is designed. Finally, the visual salience of the urban natural streets is ranked by these CVS scores and the visual hierarchy is derived by the head/tail breaks scheme. The model was applied to eight typical grid-like street networks and the results show that the performance of visual discrimination on street hierarchies is greatly improved. Our hierarchy generation method could effectively detect visually prominent streets for grid-like street networks and generate the visual hierarchies of grid-like street networks that conform to the hierarchies perceived by human eyes. These results would provide helpful suggestions in practical urban street network applications.

Original languageEnglish (US)
Article number101454
JournalComputers, Environment and Urban Systems
Volume80
DOIs
StatePublished - Mar 2020

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urban planning
skeleton
imagery
sensor
urban research
stroke
method
discrimination
resident
cause
performance
index
city
urban study

Keywords

  • Grid-like urban street
  • Hierarchy generation
  • Relative salience
  • Visual attention

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Ecological Modeling
  • Environmental Science(all)
  • Urban Studies

Cite this

Capturing what human eyes perceive : A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks. / Zhen, Wenjie; Yang, Lin; Kwan, Mei Po; Zuo, Zejun; Wan, Bo; Zhou, Shunping; Li, Shengwen; Ye, Yaqin; Qian, Haoyue; Pan, Xiaofang.

In: Computers, Environment and Urban Systems, Vol. 80, 101454, 03.2020.

Research output: Contribution to journalArticle

Zhen, Wenjie ; Yang, Lin ; Kwan, Mei Po ; Zuo, Zejun ; Wan, Bo ; Zhou, Shunping ; Li, Shengwen ; Ye, Yaqin ; Qian, Haoyue ; Pan, Xiaofang. / Capturing what human eyes perceive : A visual hierarchy generation approach to emulating saliency-based visual attention for grid-like urban street networks. In: Computers, Environment and Urban Systems. 2020 ; Vol. 80.
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