Application for Video Analysis Based on Machine Learning and Computer Vision Algorithms

An application for video data analysis based on computer vision methods is presented. The proposed system consists of five consecutive stages: face detection, face tracking, gender recognition, age classification and statistics analysis. AdaBoost classifier is utilized for face detection. A modification of Lucas and Kanade algorithm is introduced on the stage of tracking. Novel gender and age classifiers based on adaptive features and support vector machines are proposed. All the stages are united into a single system of audience analysis. The proposed software complex can find its applications in different areas, from digital signage and video surveillance to automatic systems of accident prevention and intelligent human-computer interfaces.