Assessing User Behaviour in News Video Retrieval

The results of a study are presented, in which people queried a news archive using an interactive video retrieval system. 242 search sessions by 39 participants on 24 topics were assessed. Before, during and after the study, participants filled in questionnaires about their expectations of a search. The questionnaire data, logged user actions on the system, queries formulated by users, and a quality measure of each search were studied. The results of the study show that topics concerning 'specific' people or objects were better retrieved than topics concerning 'general' objects and scenes. Users were able to estimate the overall quality of a search but did not know when the optimal result was reached within the search process. Analysis of the results at various stages in the retrieval process suggests that retrieval based on transcriptions of the speech in video data adds more to the average precision of the result than content-based image retrieval based on low-level visual features. The latter is particularly useful in providing the user with an overview of the dataset and thus an indication of the success of a search. Based on the results, implications for the design of user interfaces of video retrieval systems are discussed.

[1]  Thomas K. Landauer,et al.  Latent Semantic Analysis , 2006 .

[2]  Corinne Jörgensen,et al.  Attributes of Images in Describing Tasks , 1998, Inf. Process. Manag..

[3]  Paul Over,et al.  The TREC VIdeo Retrieval Evaluation (TRECVID): A Case Study and Status Report , 2004, RIAO.

[4]  Marcel Worring,et al.  Optimizing similarity based visualization in content based image retrieval , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[5]  Gary Marchionini,et al.  The relative effectiveness of concept-based versus content-based video retrieval , 2004, MULTIMEDIA '04.

[6]  Antonio C. Siochi,et al.  A State Transition Analysis of Image Search Patterns on the web , 2003, CIVR.

[7]  Paul Over,et al.  TRECVID 2003 - an overview , 2003 .

[8]  John R. Smith,et al.  Modal Keywords, Ontologies, and Reasoning for Video Understanding , 2003, CIVR.

[9]  Johan Oomen,et al.  BIRTH: BUILDING AN INTERACTIVE RESEARCH AND DELIVERY NETWORK FOR TELEVISION HERITAGE , 2004 .

[10]  Timo Ojala,et al.  TRECVID 2003 Experiments at Media Team Oulu and VTT , 2003, TRECVID.

[11]  João Magalhães,et al.  Video Retrieval Using Search and Browsing , 2004, TRECVID.

[12]  Jean-Luc Gauvain,et al.  The LIMSI Broadcast News transcription system , 2002, Speech Commun..

[13]  Marcel Worring,et al.  Accessing video archives using interactive search , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[14]  Eero Hyvönen,et al.  A Cultural Community Portal for Publishing Museum Collections on the Semantic Web , 2004, ECAI Workshop on Application of Semantic Web Technologies to Web Communities.

[15]  Marcel Worring,et al.  Classification of user image descriptions , 2004, Int. J. Hum. Comput. Stud..

[16]  Peter G. B. Enser,et al.  Analysis of user need in image archives , 1997, J. Inf. Sci..

[17]  Gavriel Salvendy,et al.  Keyword comparison: a user-centered feature for improving web search tools , 2000, Int. J. Hum. Comput. Stud..

[18]  Tobun Dorbin Ng,et al.  Informedia at TRECVID 2003 : Analyzing and Searching Broadcast News Video , 2003, TRECVID.

[19]  Alexander G. Hauptmann,et al.  Successful approaches in the TREC video retrieval evaluations , 2004, MULTIMEDIA '04.

[20]  Michael G. Christel,et al.  Finding the right shots: assessing usability and performance of a digital video library interface , 2004, MULTIMEDIA '04.

[21]  Pamela Briggs,et al.  Image Retrieval Interfaces: A User Perspective , 2004, CIVR.

[22]  J. G. Schuurman,et al.  Video Content Foraging , 2004, CIVR.

[23]  Marcel Worring,et al.  User Strategies in Video Retrieval: A Case Study , 2004, CIVR.

[24]  John R. Smith,et al.  IBM Research TRECVID-2009 Video Retrieval System , 2009, TRECVID.

[25]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[26]  Alan F. Smeaton,et al.  Dublin City University Video Track Experiments for TREC 2002 , 2001, TREC.

[27]  Dennis Koelma,et al.  The MediaMill TRECVID 2008 Semantic Video Search Engine , 2008, TRECVID.