Gait Recognition from Highly Compressed Videos

arXiv:2404.12183v1 Announce Type: new
Abstract: Surveillance footage represents a valuable resource and opportunities for conducting gait analysis. However, the typical low quality and high noise levels in such footage can severely impact the accuracy of pose estimation algorithms, which are foundational for reliable gait analysis. Existing literature suggests a direct correlation between the efficacy of pose estimation and the subsequent gait analysis results. A common mitigation strategy involves fine-tuning pose estimation models on noisy data to improve robustness. However, this …

abstract accuracy algorithms analysis arxiv correlation cs.cv foundational however impact literature low noise opportunities quality recognition surveillance type videos