Decoding social interaction to understand traumatic behaviours in social dynamics
Pritesh Nalinbhai Contractor · 2025
This research aims to better understand human behaviour in social environment by using computer vision and large language models (LLMs), [33] [34], with a focus on understanding the traumatic behaviour of person such as avoidance, dissociation, social withdrawal, and physical reflections contributing trembling that has experienced by an individual following exposure to distressing or series of such events including physical assault, witnessing accident experiencing personal loss or enduring natural disaster, using multi-modal cues like visual or audio data captured through surveillance data. A mixed-methods approach will be adopted. The qualitative component involves the evaluation of existing datasets, algorithms, and AI integration, while the quantitative aspect focuses on modelling social interaction factors [4], including nonverbal cues like gesture, pose estimation, trajectory derived from the literature [24], [10], [22], [11], [25], [20], [21]