Identification de personnes dans des flux multimédia.

This paper describes a multi-modal person recognition system for video broadcast developed for participating to the REPERE challenge, that was organized jointly by the DGA and the ANR (French Research National Agency). The main track of this challenge targets the identification of all persons occurring in a video either. The main scientific issue addressed by this challenge is the combination of audio and video information extraction processes for improving the extraction performance in both modalities. In this paper, we present a strategy for speaker identification based on enriching the speaker diarization by features related to the ”understanding” of the video scenes: text overlay transcription and analysis, automatic situation identification (TV set, report), the amount of people visible, TV set disposition and even the camera when available. Experiments on the REPERE corpus show interest of the proposed approach.