A computer vision problem termed as Human ac- tion imitation aims to estimate human body movements and demonstrates how the joints are related. Because it has somany implications for the automatic retrieval of films of indi- vidual behaviors using visual elements, human action imitation has gained in popularity. Human categorization, extraction of features, and activity detection are among the most frequent action imitation phases. In the domains of video surveillance, human-computer interaction, virtual reality, etc., human action imitation has important theoretical implications and numerous application possibilities. To distinguish human actions, thefootage is exhibited as Content-Based Video Retrieval (CBVR). The Gait Classifier mechanism and DBSCAN (DensityBased Spatial Clustering of Applications with Noise) are utilised to replicatethe gestures of the individual. Even though DBSCAN is being used to optimize clustering performance, gait analysis is frequently used within medical care to assistance in comprehending the gaitactions.