Urban Mindscape: Bridging the Subjective and Objective Perception in Proximate Sensing

Urban Mindscape: Bridging the Subjective and Objective Perception in Proximate Sensing

Jan 2024 - May 2024

Urban Perception; Semantic Segmentation; Street View Images; Convolutional Neural Network (CNN); Deep Learning

Street view images (SVI) have become an important source to estimate urban visual features and human perception (Biljecki and Ito, 2021). When combined with merging technologies like computer vision (CV), SVI have shown great explanatory capability in terms of objective features analysis and subjective perception assessment. However, few researches were conducted to explore the intrinsic relations between subjective and objective connotations, especially in Global South where more irregularity in the formal character of the space(Yu et al., 2024). This research focuses on the following three questions. How does the objective visual composition of street space affect subjective human emotional perceptions? The suitability of small towns in developing regions for a data- and technology-driven spatial quality research paradigm? How generalizable are the models under this research framework in different contexts across the globe?

Type: Academic Work | Geospatial Machine Learning in Remote Sensing
Role: Individual Research
Location: Paipa, Colombia
Date: January, 2024 - May, 2024

Presentation