@conference {cLe,
	title = {Towards large scale multimedia indexing: A case study on person discovery in broadcast news},
	booktitle = {International Workshop on Content-Based Multimedia Indexing - CBMI 2017},
	year = {2017},
	month = {06/2017},
	address = {Firenze, Italy},
	abstract = {<p class="p1">The rapid growth of multimedia databases and the human interest in their peers make indices representing the location and identity of people in audio-visual documents essential for searching archives. Person discovery in the absence of prior identity knowledge requires accurate association of audio-visual cues and detected names. To this end, we present 3 different strategies to approach this problem: clustering-based naming, verification-based naming, and graph-based naming. Each of these strategies utilizes different recent advances in unsupervised face / speech representation, verification, and optimization. To have a better understanding of the approaches, this paper also provides a quantitative and qualitative comparative study of these approaches using the associated corpus of the Person Discovery challenge at MediaEval 2016. From the results of our experiments, we can observe the pros and cons of each approach, thus paving the way for future promising research directions.</p>},
	author = {Nam Le and Herv{\'e} Bredin and Gabriel Sargent and Miquel India and Paula Lopez-Otero and Claude Barras and Camille Guinaudeau and Guillaume Gravier and Gabriel Barbosa da Fonseca and Izabela Lyon Freire and Zenilton Patroc{\'\i}nio Jr. and Silvio Jamil F. Guimaraes and Gerard Mart{\'\i} and Morros, J.R. and Javier Hernando and Laura Docio-Fernandez and Carmen Garcia-Mateo and Sylvain Meignier and Jean-Marc Odobez}
}
@conference {cPoignant16,
	title = {The CAMOMILE Collaborative Annotation Platform for Multi-modal, Multi-lingual and Multi-media Documents},
	booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
	year = {2016},
	month = {05/2016},
	address = {Portoro{\v z} (Slovenia)},
	abstract = {<p>In this paper, we describe the organization and the implementation of the CAMOMILE collaborative annotation framework for multimodal, multimedia, multilingual (3M) data. Given the versatile nature of the analysis which can be performed on 3M data, the structure of the server was kept intentionally simple in order to preserve its genericity, relying on standard Web technologies. Layers of annotations, defined as data associated to a media fragment from the corpus, are stored in a database and can be managed through standard interfaces with authentication. Interfaces tailored specifically to the needed task can then be developed in an agile way, relying on simple but reliable services for the management of the centralized annotations. We then present our implementation of an active learning scenario for person annotation in video, relying on the CAMOMILE server; during a dry run experiment, the manual annotation of 716 speech segments was thus propagated to 3504 labeled tracks. The code of the CAMOMILE framework is distributed in open source.</p>},
	keywords = {active learning, Annotation tool, collaborative annotation, multimedia, person annotation},
	isbn = {978-2-9517408-9-1},
	url = {http://www.lrec-conf.org/proceedings/lrec2016/pdf/456_Paper.pdf},
	author = {Johann Poignant and Mateusz Budnik and Herv{\'e} Bredin and Claude Barras and Mickael Stefas and Pierrick Bruneau and Gilles Adda and Laurent Besacier and Hazim Ekenel and Gil Francopoulo and Javier Hernando and Joseph Mariani and Morros, J.R. and Georges Qu{\'e}not and Sophie Rosset and Thomas Tamisier}
}
