Christine Sénac

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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)
Audio-Visual People Diarization (AVPD) is an original framework that simultaneously improves audio, video, and audiovisual diarization results. Following a literature review of people diarization for both audio and video content and their limitations, which includes our own contributions, we describe a proposed method for associating both audio and video(More)
In this paper, we investigate new approaches to improve speech activity detection, speaker segmentation and speaker clustering. The main idea behind them is to deal with the problem of speaker diarization for meetings where error rates are relatively high. In opposition to existing methods, a new iterative scheme is proposed considering those three tasks as(More)
This paper describes a new scheme for robust speech recognition systems where visual information and acoustic features are merged. Using as robust unit the « pseudo-diphone », we compare a global Hidden Markov Model (HMM) and a Master/Slave HMM through a centisecond preprocessing and through a segmental one. We confirm by experimentation the importance of(More)
Multiple sub-stories usually coexist in every episode of a TV series. We propose several variants of an approach for plot de-interlacing based on scenes clustering – with the ultimate goal of providing the end-user with tools for fast and easy overview of one episode, one season or the whole TV series. Each scene can be described in three different ways(More)
Recent TV series tend to have more and more complex plot. They follow the lives of numerous characters and are made of multiple intertwined stories. In this paper, we introduce StoViz, a web-based interface allowing a fast overview of this kind of episode structure, based on our plot de-interlacing system. StoViz has two main goals. First, it provides the(More)