Machine-based understanding of manually collected visual and auditory datasets for urban perception studies

摘要

While the previous studies have attempted to quantify the environmental characteristics which stimulate different emotions and perceptions, the temporal aspect of the transient urbanscapes and the multimodality in data collection and analysis has not been given enough attention. The characteristics of the urban environment fluctuate with the time, time-based sensory data collection is, therefore, critical for comprehensive assessment of the surroundings. This research note aims to propose a methodology for the temporal and multimodal data collection and demonstrates the use of smartphone-based camera and handheld recorder to manually collect visual and audio datasets simultaneously from urban streets. It utilizes state of the art computer algorithms to extract attributes from the visual and auditory datasets which can further help in establishing comparison and relationships between different urban spaces. Altogether, this study proposes an idea and working proof presenting data collection and automated analysis which can aid decision makers and urban planners to create a lively, safe and healthy environment.