Huge amounts of multimedia data have been generated in recent years, either through profesional “content providers” (TV, movies, internet TV, and music videos) or user-generated content (vlogs, social media multimodal content, and multisensor data). Therefore, the need for automatic indexing, classification, content visualization, and recommendation, through multimodal pattern recognition, is obvious for various applications. In addition, multimedia data exhibit much richer structures and representations than simple forms of data and, as a result, the related pattern recognition approaches must take that into consideration.

This Special Issue focuses on novel approaches for analyzing multimodal content using pattern recognition and signal analysis algorithms. Application areas include but are not limited to video summarization, content-based multimedia indexing and retrieval, content-based recommender systems, multimodal behavior and emotion recognition, patient/elderly home monitoring based on multimodal sensors, mental health monitoring, and autonomous driving.

In this Special Issue, we invite submissions that report on cutting-edge research in the broad spectrum of pattern recognition in multimedia analysis, related to the aforementioned areas. Survey papers and reviews in a specific research and/or application area are also welcome. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in open-access format in Applied Sciences and collected together on this Special Issue website.

Dr. Theodoros Giannakopoulos
Prof. Dr. Evaggelos Spyrou
Guest Editors