Towards large scale multimedia indexing: a case study on person discovery in broadcast news
Document typeConference report
PublisherAssociation for Computing Machinery (ACM)
Rights accessRestricted access - publisher's policy
European Commisision's projectEUMSSI - EUMSSI- Event Understanding through Multimodal Social Stream Interpretation (EC-FP7-611057)
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.
CitationLe, N., Bredin, H., Sergent, G., India, M., López-Otero, P., Barras, C., Guinaudeau, C., Gravier, G., Barbosa da Fonseca, G., Lyon Freire, I., Patrocinio Jr., Z., Jamil F. Guimarães, S., Marti, G., Morros, J.R., Hernando, J., Docio-Fernández, L., García-Mateo, C., Meignier, S., Odobez, J. Towards large scale multimedia indexing: a case study on person discovery in broadcast news. A: International Workshop on Content-Based Multimedia Indexing. "Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, CBMI 2017, Florence, Italy, June 19-21, 2017". Firenze: Association for Computing Machinery (ACM), 2017, p. 1-6.