UPC System for the 2016 MediaEval Multimodal Person Discovery in Broadcast TV task
نویسندگان
چکیده
The UPC system works by extracting monomodal signal segments (face tracks, speech segments) that overlap with the person names overlaid in the video signal. These segments are assigned directly with the name of the person and used as a reference to compare against the non-overlapping (unassigned) signal segments. This process is performed independently both on the speech and video signals. A simple fusion scheme is used to combine both monomodal annotations into a single one.
منابع مشابه
Tokyo Tech at MediaEval 2016 Multimodal Person Discovery in Broadcast TV task
This paper describes our diarization system for the Multimodal Person Discovery in Broadcast TV task of the MediaEval 2016 Benchmark evaluation campaign [1]. The goal of this task is naming speakers, who are appearing and speaking simultaneously in the video, without prior knowledge. Our diarization system relies on face diarization approach. We extract deep features from a face every 0.5 secon...
متن کاملGTM-UVigo System for Multimodal Person Discovery in Broadcast TV Task at MediaEval 2016
In this paper, we present the system developed by GTMUVigo team for the Multimedia Person Discovery in Broadcast TV task at MediaEval 2016. The proposed approach consists in a novel strategy for person discovery which is not based on speaker and face diarisation as in previous works. In this system, the task is approached as a person recognition problem: there is an enrolment stage, where the v...
متن کاملUPC System for the 2015 MediaEval Multimodal Person Discovery in Broadcast TV task
This paper describes a system to identify people in broadcast TV shows in a purely unsupervised manner. The system outputs the identity of people that appear, talk and can be identified by using information appearing in the show (in our case, text with person names). Three types of monomodal technologies are used: speech diarization, video diarization and text detection / named entity recogniti...
متن کاملPERCOLATTE : A Multimodal Person Discovery System in TV Broadcast for the Medieval 2015 Evaluation Campaign
This paper describes the PERCOLATTE participation to MediaEval 2015 task: “Multimodal Person Discovery in Broadcast TV” which requires developing algorithms for unsupervised talking face identification in broadcast news. The proposed approach relies on two identity propagation strategies both based on document chaptering and restricted overlaid names propagation rules. The primary submission sh...
متن کاملMultimodal Person Discovery in Broadcast TV at MediaEval 2016
We describe the“Multimodal Person Discovery in Broadcast TV” task of MediaEval 2016 benchmarking initiative. Participants are asked to return the names of people who can be both seen as well as heard in every shot of a collection of videos. The list of people is not known a priori and their names has to be discovered in an unsupervised way from media content using text overlay or speech transcr...
متن کامل