Evaluation of Multimedia Retrieval Systems

In this chapter, we provide the tools and methodology for comparing the effectiveness of two or more multimedia retrieval systems in a meaningful way. Several aspects of multimedia retrieval systems can be evaluated without consulting the potential users or customers of the system, such as the query processing time (measured for instance in milliseconds per query) or the query throughput (measured for instance as the number of queries per second). In this chapter, however, we will focus on aspects of the system that influence the effectiveness of the retrieved results. In order to measure the effectiveness of search results, one must at some point consult the potential user of the system. For, what are the correct results for the query “black jaguar”? Cars, or cats? Ultimately, the user has to decide.

[1]  Jitendra Malik,et al.  Color- and texture-based image segmentation using EM and its application to content-based image retrieval , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[2]  Paul Over,et al.  TRECVID: evaluating the effectiveness of information retrieval tasks on digital video , 2004, MULTIMEDIA '04.

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

[4]  Thijs Westerveld,et al.  The INEX 2006 Multimedia Track , 2006, INEX.

[5]  Jonathan G. Fiscus,et al.  NIST's 1998 topic detection and tracking evaluation (TDT2) , 1999, EUROSPEECH.

[6]  Mark Sanderson,et al.  The CLEF 2004 Cross-Language Image Retrieval Track , 2004, CLEF.

[7]  James Ze Wang,et al.  Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Nuno Vasconcelos,et al.  A probabilistic architecture for content-based image retrieval , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[9]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[10]  David A. Forsyth,et al.  Matching Words and Pictures , 2003, J. Mach. Learn. Res..

[11]  Mark Sanderson,et al.  The CLEF Cross Language Image Retrieval Track (ImageCLEF) 2004 , 2004, CLEF.

[12]  R. Manmatha,et al.  Automatic image annotation and retrieval using cross-media relevance models , 2003, SIGIR.

[13]  Emmanuel Vincent,et al.  The 2005 Music Information retrieval Evaluation Exchange (MIREX 2005): Preliminary Overview , 2005, ISMIR.

[14]  A. P. deVries,et al.  Experimental evaluation of a generative probabilistic image retrieval model on 'easy' data , 2003 .

[15]  David A. Forsyth,et al.  Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary , 2002, ECCV.

[16]  O. Ratib,et al.  Integration of a multimedia teaching and reference database in a PACS environment. , 2002, Radiographics : a review publication of the Radiological Society of North America, Inc.

[17]  Norbert Fuhr,et al.  Advances in XML information retrieval and evaluation : 4th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2005, Dagstuhl Castle, Germany, November 28-30, 2005 : revised selected papers , 2006 .

[18]  José Luis Vicedo González,et al.  TREC: Experiment and evaluation in information retrieval , 2007, J. Assoc. Inf. Sci. Technol..

[19]  Thierry Pun,et al.  The Truth about Corel - Evaluation in Image Retrieval , 2002, CIVR.

[20]  Justin Zobel,et al.  How reliable are the results of large-scale information retrieval experiments? , 1998, SIGIR '98.

[21]  Michael I. Jordan,et al.  Modeling annotated data , 2003, SIGIR.

[22]  Thierry Pun,et al.  Performance evaluation in content-based image retrieval: overview and proposals , 2001, Pattern Recognit. Lett..

[23]  Stephen E. Robertson Evaluation in Information Retrieval , 2000, ESSIR.

[24]  Margaret King,et al.  Evaluation of natural language processing systems , 1991 .

[25]  Gabriella Kazai,et al.  INEX 2005 Multimedia Track , 2005, INEX.

[26]  David A. Hull Using statistical testing in the evaluation of retrieval experiments , 1993, SIGIR.

[27]  Joshua R. Smith,et al.  Image retrieval evaluation , 1998, Proceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173).

[28]  Jean M. Tague,et al.  The pragmatics of information retrieval experimentation , 1981 .

[29]  G. P. Nguyen,et al.  The MediaMill TRECVID 2005 Semantic Video Search Engine (Draft Version). , 2005 .