RETRACTED: Gait Analysis of Pedestrians with the Aim of Detecting Disabled People

Gait classification is an effective and non-intrusive method for human identification and it has received significant attention in the recent years due to its applications in visual surveillance and monitoring systems. In this project, we analysed gait signatures using spatio-temporal motion characteristics of a person to answer the question ``is there a discriminating feature in gait signal that can help to categorise disable person from healthy''. The procedure has three steps. detection of a pedestrian using YOLO followed by the silhouette extraction using the Gaussian Mixture Model (GMM). Finally, skeletonization from the silhouette image to estimate head and torso locations and their angles with the vertical axis. Furthermore, velocity and acceleration signals were recorded to look for accelerating behaviour of person walking with a limp.