Sports Scene Detection in TV News Video Using Variant AdaBoost Classifier

This paper proposes a method for detecting sports scenes using variant AdaBoost classifier.In the approach,sports scenes in TV news are initially classified into three types: on grass,ice or snow and man-made floors.Three low-level image features of color histogram,edge direction histogram and co-occurrence matrix texture are extracted.The focus of this paper is on the use of the boosting method for automatic selection of features and classification.For each type of sports scenes,it builds a classifier based on AdaBoost using low-level image features above.The category confidence scores of each image calculated by each classifier are then combined into the final result.The paper applies the system on the extraction task of semantic feature “Sports Event” of TRECVID2003.It works effectively and gives high precision.