Unsupervised Feature Selection for Detection Using Mutual Information Thresholding

摘要

This paper proposes a method for unsupervised selection of features for detecting important events in a surveillance context. While traditional feature selection requires manually annotated ground truth to choose the best features, we examine the possibil