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The IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes our participation to the TRECVID 2010 semantic indexing and instance search tasks. For the semantic indexing task, we evaluated a number of different descriptors and tried different fusion strategies, in particular hierarchical fusion. The best(More)
! A_CU-run6: local feature alone – average fusion of 3 SVM classification results for each concept using various feature representation choices. ! A_CU-run5: linear weighted fusion of A_CU-run6 with two grid-based global features (color moment and wavelet texture). ! A_CU-run4: linear weighted fusion of A_CU-run5 with a SVM classification result using(More)
I4U is a joint entry of nine research Institutes and Universities across 4 continents to NIST SRE 2012. It started with a brief discussion during the Odyssey 2012 workshop in Singapore. An online discussion group was soon set up, providing a discussion platform for different issues surrounding NIST SRE'12. Noisy test segments, uneven multi-session training,(More)
Content-based people clustering is a crucial step for people indexing within video documents. In this paper, we investigate the use of both face and clothing features. A method of extracting a <i>keyface</i> for each video sequence is proposed. An algorithm based on the average of the <i>N</i>-minimum pair distances between local invariant features is used(More)
Automatic face recognition in unconstrained environments is a challenging task. To test current trends in face recognition algorithms, we organized an evaluation on face recognition in mobile environment. This paper presents the results of 8 different participants using two verification met-rics. Most submitted algorithms rely on one or more of three types(More)
In this paper, we describe a new application for multimedia indexing, using a system that monitors the instrumental activities of daily living to assess the cognitive decline caused by dementia. The system is composed of a wearable camera device designed to capture audio and video data of the instrumental activities of a patient, which is leveraged with(More)
This paper presents the LIUM open-source speaker diarization toolbox, mostly dedicated to broadcast news. This tool includes both Hierarchical Agglomerative Clustering using well-known measures such as BIC and CLR, and the new ILP clustering algorithm using i-vectors. Diarization systems are tested on the French evaluation data from ESTER, ETAPE and REPERE(More)
We investigate the problem of audiovisual (AV) person di-arization in broadcast data. That is, automatically associate the faces and voices of people and determine when they appear or speak in the video. The contributions are twofolds. First, we formulate the problem within a novel CRF framework that simultaneously performs the AV association of voices and(More)
This paper examines the issue of face, speaker and bi-modal authentication in mobile environments when there is significant condition mismatch. We introduce this mismatch by enrolling client models on high quality biometric samples obtained on a laptop computer and authenticating them on lower quality biomet-ric samples acquired with a mobile phone. To(More)
The availability of many independent services on an open network opens the opportunity of composing individual instances to achieve complex functionality. Most often there are several possible compositions to achieve the same high-level functionality; the advantage of choosing one composition instead of another one may lie in the different quality of the(More)