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Affective Content Analysis' most important aims are to quickly access a favourite movie from a vast list, efficiently access sports highlights or obtain summaries of movies. The concept consists on classifying segments of audiovisual contents according to the level of excitement and pleasure they convey. The features presented in this book are designed to extract information from videos and convert it into descriptions of the amount or type of affect. This book focuses on the creation and validation of video features, more specifically motion and colour features, based on psychological background studies. The experimental tests developed reveal positive results for most of the features proposed, mainly for the Motion Entropy feature. While in Cognitive Analysis there are various algorithms to detect the innumerable specific events, the best advantage of Affective Analysis is that these algorithms can be replaced by one model that analyses affect in the entire media file. In addition, Affective Content influences the attention of a user, as well as his evaluation and memory of the Cognitive Content, depending on the current mood being invoked on the viewer.