The COST292 Experimental Framework for Rushes Summarization Task in TRECVID 2008

Umut Naci (1) , Uros Damnjanovic (2) , Boris Mansencal (3) , Jenny Benois-Pineau (3) , Christian Kaes (3) , Marzia Corvaglia (4) , Eliana Rossi (4) , Naiara Aginako (5)

1 TU Delft - Delft University of Technology
2 QMUL - Queen Mary University of London
3 LaBRI - Laboratoire Bordelais de Recherche en Informatique
4 UniBs - Università degli Studi di Brescia = University of Brescia
5 VicomTech

In this paper, the method used for Rushes Summarization task by the COST 292 consortium is reported. The approach proposed this year differs significantly from the one proposed in the previous years because of the introduction of new processing steps, like repetition detection in scenes. The method starts with junk frames removal and follows with clustering and scene detection; then for each scene, repetitions are detected in order to extract once the real scene; the following step consists in face detections (faces are considered semantically relevant) and in pan, tilt and zoom detections (other camera motions are usually related to technical operations in the backstage); finally the summary is extracted.

Mots clés: repetition detection; spectral clustering; normalized cuts; mid-level features

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Umut Naci, Uros Damnjanovic, Boris Mansencal, Jenny Benois-Pineau, Christian Kaes, et al.. The COST292 Experimental Framework for Rushes Summarization Task in TRECVID 2008. TVS'08 (Trec Video Summarization), Oct 2008, Vancouver, Canada. pp.40, ⟨10.1145/1463563.1463569⟩. ⟨hal-00351993⟩