Automatic Signer Diarization - The Mover Is the Signer Approach

Binyam Gebrekidan Gebre, Peter Wittenburg, Tom Heskes; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2013, pp. 283-287

Abstract

We present a vision-based method for signer diarization the task of automatically determining "who signed when?" in a video. This task has similar motivations and applications as speaker diarization but has received little attention in the literature. In this paper, we motivate the problem and propose a method for solving it. The method is based on the hypothesis that signers make more movements than their interlocutors. Experiments on four videos (a total of 1.4 hours and each consisting of two signers) show the applicability of the method. The best diarization error rate (DER) obtained is 0.16.

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[bibtex]
@InProceedings{Gebre_2013_CVPR_Workshops,
author = {Gebre, Binyam Gebrekidan and Wittenburg, Peter and Heskes, Tom},
title = {Automatic Signer Diarization - The Mover Is the Signer Approach},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2013}
}