| Titre : | Semantic video fingerprinting and retrieval using face information |
| Auteurs : | Costas Cotsaces, Auteur ; Nikos Nikolaidis, Auteur ; Ioannis Pitas, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Signal processing. Image communication (Vol. 24 N° 7, Août 2009) |
| Article en page(s) : | pp. 598-613 |
| Note générale : | Electronique |
| Langues : | Anglais |
| Index. décimale : | 621.382 (Dispositifs électroniques utilisant les effets des corps solides. Dispositifs semi-conducteurs) |
| Tags : | Video fingerprinting retrieval Face recognition Semantic features |
| Résumé : |
The management of large video databases, especially those containing motion picture and television data, is a major contemporary challenge.
A very significant tool for this management is the ability to retrieve those segments that are perceptually similar to a query segment. Another similar but equally important task is determining if a query segment is a (possibly modified) copy of part of a video in the database. The basic way to perform these two tasks is to characterize each video segment with a unique representation called a signature. Using semantic information for the construction of the signatures is a good way to ensure robustness in retrieval and fingerprinting. Here a ubiquitous semantic feature, namely the existence and identity of human faces, will be used to construct the signature. A fast algorithm has been developed to quickly and robustly perform these two tasks on very large video databases. The prerequisite face recognition was performed by a commercial system. Having verified the basic efficacy of our algorithm on a database of real video from motion pictures and television series, we then proceed to further explore its performance in an artificial digital video database, which was created using a probabilistic model of the video creation process. This enabled us to explore variations in performance based on parameters that were impossible to control in a real video database. Furthermore, the suitability of the proposed approach for very large databases was tested using (artificial) data corresponding to hundreds or thousands of hours of video. |
| DEWEY : | 361.382 |
| ISSN : | 0923-5965 |
| En ligne : | http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%235640%232009%23999759992%231387057%23FLA%23&_cdi=5640&_pubType=J&_auth=y&_acct=C000070790&_version=1&_urlVersion=0&_userid=6909337&md5=ef50f0354a8bd89dd240b9fe36304745 |
