Abstract
AbstractAn application for video data analysis based on computer vision methods is presented in this chapter. The proposed system consists of five consecutive stages: face detection, face tracking, gender recognition, age classification, and statistics analysis. The AdaBoost classifier is utilized for face detection. A modification of Lucas and Kanade algorithm is introduced on the stage of face tracking. Novel gender and age classifiers based on adaptive features and support vector machines are proposed. More than 90 % accuracy of viewer’s gender recognition is achieved. All stages are united into a single system of audience analysis. The system allows to extract all possible information about depicted people from the input video stream, aggregate and analyze this information in order to measure different statistical parameters. The proposed software solution can find its applications in different areas, from digital signage and video surveillance to the automatic systems of accident prevention and intelligent human-computer interfaces.KeywordsImage recognitionFace detectionGender classificationAge estimationMachine learningObject trackingSupport vector machines
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