A study of behavioural characteristics of the elderly based on computer vision technology
Wang Lei, Wenqi He · International Journal of Urban Sciences · 2025
The study of elderly behavior characteristics holds significant importance for enhancing the quality of urban spaces and improving the quality of life for the elderly. Utilizing computer vision technology for acquiring behavioral data offers greater efficiency. However, current computer vision methods that specifically recognize different behaviors of the elderly population face certain challenges. This paper aims to explore methods for analyzing elderly behavior characteristics based on computer vision technology, in the hope of providing a scientific basis for the optimization of urban spaces for the elderly. The study constructs a computer vision behavior detection algorithm to effectively recognize six types of behaviors in the elderly (exercise, jogging, sitting, standing, walking, and playing chess or cards). Subsequently, it analyzes statistical data on elderly behavior to investigate the behavioral characteristics of the elderly in public spaces. The findings indicate that computer vision technology can provide a new perspective and an efficient solution for the field of elderly behavior analysis. The outdoor activities of the elderly exhibit significant temporal regularity and spatial variability, offering technical support for the optimization of urban spaces.