""In this work the authors propose a classification method based on Support Vector Machine (SVM) and key frames features extraction to classify historical sport video contents. In the context of the Italian Project, IRMA (Information Retrieval in Multimedia Archives), with the goal to recover and preserve historical videos of proven cultural interest, a data set made up of several hours of videos from the 1960 Olympic games, provided by RAI and Teche RAI, is adopted as testbed. Each video is summarized by its key frames and represented by the features vectors computed in the Laguerre Gauss transformed domain. The high-level video classification starts from these vectors that are the input of the SVM classifier. The experimental results show the effectiveness of the proposed method.""
Capodiferro, L., Costantini, L., Mangiatordi, F., Pallotti, E. (2012). SVM for historical sport video classification. In Communications Control and Signal Processing (ISCCSP) (pp.1-4) [10.1109/ISCCSP.2012.6217817].
SVM for historical sport video classification
MANGIATORDI, Federica;PALLOTTI, EMILIANO
2012-01-01
Abstract
""In this work the authors propose a classification method based on Support Vector Machine (SVM) and key frames features extraction to classify historical sport video contents. In the context of the Italian Project, IRMA (Information Retrieval in Multimedia Archives), with the goal to recover and preserve historical videos of proven cultural interest, a data set made up of several hours of videos from the 1960 Olympic games, provided by RAI and Teche RAI, is adopted as testbed. Each video is summarized by its key frames and represented by the features vectors computed in the Laguerre Gauss transformed domain. The high-level video classification starts from these vectors that are the input of the SVM classifier. The experimental results show the effectiveness of the proposed method.""I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
