Key Frame Detection Based Semantic Event Detection and Classification Using Heirarchical Approach for Cricket Sport Video Indexing

In this paper, we propose a key frame detection based approach towards semantic event detection and classification in cricket videos. The proposed scheme performs a top-down event detection and classification using hierarchical tree. At level 1, we extract key frames for indexing based upon the Hue Histogram difference. At level 2, we detect logo transitions and classify the frames as realtime or replay fragments. At level 3, we classify the realtime frames as field view, pitch view or non field view based on colour features such as soil colour for pitch view and grass colour for field view. At level 4, we detect close up and crowd frames based upon edge detection. At level 5a, we classify the close up frames into player of team A, player of team B and umpire based upon skin colour and corresponding jersey colour. At level 5b, we classify the crowd frames into spectators, player's gathering of team A or player's gathering of team B. Our classifiers show excellent results with correct detection and classification with reduced processing time.