@inbook {bCarcel12, title = {Rich Internet Application for Semi-automatic Annotation of Semantic Shots on Keyframes}, booktitle = {Computational Intelligence for Multimedia Understanding}, volume = {7242}, number = {Lecture Notes in Computer Science}, year = {2012}, pages = {172-182}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Pisa, Italy}, abstract = {

This paper describes a system developed for the semi- automatic annotation of keyframes in a broadcasting company. The tool aims at assisting archivists who traditionally label every keyframe manually by suggesting them an automatic annotation that they can intuitively edit and validate. The system is valid for any domain as it uses generic MPEG-7 visual descriptors and binary SVM classifiers. The classification engine has been tested on the multiclass problem of semantic shot detection, a type of metadata used in the company to index new con- tent ingested in the system. The detection performance has been tested in two different domains: soccer and parliament. The core engine is accessed by a Rich Internet Application via a web service. The graphical user interface allows the edition of the suggested labels with an intuitive drag and drop mechanism between rows of thumbnails, each row representing a different semantic shot class. The system has been described as complete and easy to use by the professional archivists at the company.

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Rich Internet Application for Semi-Automatic Annotation of Semantic Shots on Keyframes from Xavi Gir{\'o}
}, keywords = {annotation, classification, MPEG-7 visual descriptors, RIA, semantic shot}, isbn = {978-3-642-32435-2}, doi = {10.1007/978-3-642-32436-9_15}, url = {http://www.springerlink.com/content/x34632125j381045/}, author = {Carcel, Elisabet and Martos, Manel and Xavier Gir{\'o}-i-Nieto and Marqu{\'e}s, F.} } @mastersthesis {x11, title = {Rich Internet Application for the Semi-Automatic Annotation of Semantic Shots on Keyframes}, year = {2011}, abstract = {

This thesis describes the graphical user interface developed for semi-automatic keyframebased semantic shot annotation and the semantic shot classifiers built. The graphical user interface aims to optimize the current indexation process by substituting manual annotation for automatic annotation and validation. The system is based on supervised learning binary classifiers and web services. The graphical user interface provides the necessary tools to fix and validate the automatic detections and to learn from the user feedback to retrain the system and improve it. Results of the classifiers evaluation, performed using cross-validation methods, show a good performance in terms of precision and recall. The graphical user interface has been described as complete and easy to use by a professional documentalist at a broadcast company.

Interfície web per l{\textquoteright}annotació semi-automàtica de plans semàntics from Xavi Gir{\'o}


}, url = {http://hdl.handle.net/2099.1/13539}, author = {Carcel, Elisabet}, editor = {Xavier Gir{\'o}-i-Nieto and Vives, X.} }