Real-Time Human Motion Detection and Tracking with Learning based Representation

Nowadays, real-time information is veryimportant and learning based human motion hasfascinated range from detection to tracking state inComputer Vision. In this system, the real-time videosare used to detect, track, and classify object or events inorder to understand a real-world scene. Video basedreal time human motion detection and tracking is acomplex and challenging task due to variation inhuman pose, shape variation, illumination changesand background appearance. A real-time mechanismis to detect the person and their moving within anenvironment from the video camera. This paperproposes human motion detection from videosequences. The proposed method includes three stages:human detection, motion tracking and accuracy resultbased on learning approach. The result is to become anefficient detection system for real-time human motion.Motion detection and tracking is determined by usingHistogram of Oriented Gradients (HOG) featureextractor and Support Vector Machine (SVM) detectorwith learning human pattern which is well performedhuman detection and tracking in video sequences.Detailed analysis is carried out on the performanceand accuracy of the system with the various test videosto show the results. The experimental resultsdemonstrate the efficiency of the metho