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* Corresponding author 1 GETALP - Groupe d’Étude en Traduction Automatique-Traitement Automatisé des Langues et de la Parole LIG - Laboratoire d-Informatique de Grenoble 2 MRIM - Modélisation et Recherche d’Information Multimédia Grenoble LIG - Laboratoire d-Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique

Abstract : We present in this article a video OCR system that detects and recognizes overlaid texts in video as well as its application to person identification in video documents. We proceed in several steps. First, text detection and temporal tracking are performed. After adaptation of images to a standard OCR system, a final post-processing combines multiple transcriptions of the same text box. The semi-supervised adaptation of this system to a particular video type video broadcast from a French TV is proposed and evaluated. The system is efficient as it runs 3 times faster than real time including the OCR step on a desktop Linux box. Both text detection and recognition are evaluated individually and through a person recognition task where it is shown that the combination of OCR and audio speaker information can greatly improve the performances of a state of the art audio based person identification system.

keyword : Video OCR text detection text recognition semi-supervised parametrization person identification

Autor: Johann Poignant - Laurent Besacier - Georges Quénot - Franck Thollard -



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