News story segmentation in the Físchlár video indexing system

This paper presents an approach to segmenting individual news stories in broadcast news programmes. The approach first performs shot boundary detection and keyframe extraction on the programme. Shots are then clustered into groups based on their colour and temporal similarity. The clustering process is controlled using the groups' statistics. After clustering, a set of criteria are applied and groups are successively eliminated in order to converge upon a set of anchorperson groups. The temporal locations of the shots in these anchorperson groups are then used to segment the programme in terms of individual news items. This work is carried out within the context of a complete video indexing, browsing and retrieval syste

TV News Story Segmentation Based on Semantic Coherence and Content Similarity

In this paper, we introduce and evaluate two novel approaches, one using video stream and the other using close-caption text stream, for segmenting TV news into stories. The segmentation of the video stream into stories is achieved by detecting anchor person shots and the text stream is segmented into stories using a Latent Dirichlet Allocation (LDA) based approach. The benefit of the proposed LDA based approach is that along with the story segmentation it also provides the topic distribution associated with each segment. We evaluated our techniques on the TRECVid 2003 benchmark database and found that though the individual systems give comparable results, a combination of the outputs of the two systems gives a significant improvement over the performance of the individual systems

Unsupervised mining of audiovisually consistent segments in videos with application to structure analysis

International audienceIn this paper, a multimodal event mining technique is proposed to discover repeating video segments exhibiting audio and visual consistency in a totally unsupervised manner. The mining strategy first exploits independent audio and visual cluster analysis to provide segments which are consistent in both their visual and audio modalities, thus likely corresponding to a unique underlying event. A subsequent modeling stage using discriminative models enables accurate detection of the underlying event throughout the video. Event mining is applied to unsupervised video structure analysis, using simple heuristics on occurrence patterns of the events discovered to select those relevant to the video structure. Results on TV programs ranging from news to talk shows and games, show that structurally relevant events are discovered with precisions ranging from 87% to 98% and recalls from 59% to 94%

Interesting faces: A graph-based approach for finding people in news

Cataloged from PDF version of article.In this study, we propose a method for finding people in large news photograph and video collections. Our method exploits the multi-modal nature of these data sets to recognize people and does not require any supervisory input. It first uses the name of the person to populate an initial set of candidate faces. From this set, which is likely to include the faces of other people, it selects the group of most similar faces corresponding to the queried person in a variety of conditions. Our main contribution is to transform the problem of recognizing the faces of the queried person in a set of candidate faces to the problem of finding the highly connected sub-graph (the densest component) in a graph representing the similarities of faces. We also propose a novel technique for finding the similarities of faces by matching interest points extracted from the faces. The proposed method further allows the classification of new faces without needing to re-build the graph. The experiments are performed on two data sets: thousands of news photographs from Yahoo! news and over 200 news videos from TRECVid2004. The results show that the proposed method provides significant improvements over textbased methods. (C) 2009 Elsevier Ltd. All rights reserve

Face detection and clustering for video indexing applications

This paper describes a method for automatically detecting human faces in generic video sequences. We employ an iterative algorithm in order to give a confidence measure for the presence or absence of faces within video shots. Skin colour filtering is carried out on a selected number of frames per video shot, followed by the application of shape and size heuristics. Finally, the remaining candidate regions are normalized and projected into an eigenspace, the reconstruction error being the measure of confidence for presence/absence of face. Following this, the confidence score for the entire video shot is calculated. In order to cluster extracted faces into a set of face classes, we employ an incremental procedure using a PCA-based dissimilarity measure in con-junction with spatio-temporal correlation. Experiments were carried out on a representative broadcast news test corpus

Dialogue scene detection in movies using low and mid-level visual features

This paper describes an approach for detecting dialogue scenes in movies. The approach uses automatically extracted low- and mid-level visual features that characterise the visual content of individual shots, and which are then combined using a state transition machine that models the shot-level temporal characteristics of the scene under investigation. The choice of visual features used is motivated by a consideration of formal film syntax. The system is designed so that the analysis may be applied in order to detect different types of scenes, although in this paper we focus on dialogue sequences as these are the most prevalent scenes in the movies considered to date

Físchlár: an on-line system for indexing and browsing broadcast television content

This paper describes a demonstration system which automatically indexes broadcast television content for subsequent non-linear browsing. User-specified television programmes are captured in MPEG-1 format and analysed using a number of video indexing tools such as shot boundary detection, keyframe extraction, shot clustering and news story segmentation. A number of different interfaces have been developed which allow a user to browse the visual index created by these analysis tools. These interfaces are designed to facilitate users locating video content of particular interest. Once such content is located, the MPEG-1 bitstream can be streamed to the user in real-time. This paper describes both the high-level functionality of the system and the low-level indexing tools employed, as well as giving an overview of the different browsing mechanisms employe