The Experts below are selected from a list of 456 Experts worldwide ranked by ideXlab platform

Susan E Webb - One of the best experts on this subject based on the ideXlab platform.

  • detection of candidatus liberibacter asiaticus in diaphorina citri and its importance in the management of citrus huanglongbing in florida
    Phytopathology, 2008
    Co-Authors: K L Manjunath, Susan E Halbert, Chandrika Ramadugu, Susan E Webb
    Abstract:

    Manjunath, K. L., Halbert, S. E., Ramadugu, C., Webb, S., and Lee, R. F. 2008. Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus huanglongbing in Florida. Phytopathology 98:387-396. Citrus huanglongbing (HLB or citrus greening), is a highly destructive disease that has been spreading in both Florida and Brazil. Its psyllid vector, Diaphorina citri Kuwayama, has spread to Texas and Mexico, thus threatening the future of citrus production elsewhere in mainland North America. Even though sensitive diagnostic methods have been developed for detection of the causal organisms, Candidatus Liberibacter spp., the pathogen cannot be detected consistently in plants until symptoms develop, presumably because of low titer and uneven distribution of the causal bacteria in nonsymptomatic tissues. In the present study, TaqMan based real-time quantitative polymerase chain reaction methodology was developed for detection of ‘Ca. L. asiaticus’ in D. citri. Over 1,200 samples of psyllid adults and nymphs, collected from various locations in Florida, from visually healthy and HLB symptomatic trees at different times of the year were analyzed to monitor the incidence and spread of HLB. The results showed that spread of ‘Ca. L. asiaticus’ in an area may be detected one to several years before the development of HLB symptoms in plants. The study suggests that discount garden centers and retail nurseries may have played a significant role in the widespread distribution of psyllids and plants carrying HLB pathogens in Florida.

K L Manjunath - One of the best experts on this subject based on the ideXlab platform.

  • detection of candidatus liberibacter asiaticus in diaphorina citri and its importance in the management of citrus huanglongbing in florida
    Phytopathology, 2008
    Co-Authors: K L Manjunath, Susan E Halbert, Chandrika Ramadugu, Susan E Webb
    Abstract:

    Manjunath, K. L., Halbert, S. E., Ramadugu, C., Webb, S., and Lee, R. F. 2008. Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus huanglongbing in Florida. Phytopathology 98:387-396. Citrus huanglongbing (HLB or citrus greening), is a highly destructive disease that has been spreading in both Florida and Brazil. Its psyllid vector, Diaphorina citri Kuwayama, has spread to Texas and Mexico, thus threatening the future of citrus production elsewhere in mainland North America. Even though sensitive diagnostic methods have been developed for detection of the causal organisms, Candidatus Liberibacter spp., the pathogen cannot be detected consistently in plants until symptoms develop, presumably because of low titer and uneven distribution of the causal bacteria in nonsymptomatic tissues. In the present study, TaqMan based real-time quantitative polymerase chain reaction methodology was developed for detection of ‘Ca. L. asiaticus’ in D. citri. Over 1,200 samples of psyllid adults and nymphs, collected from various locations in Florida, from visually healthy and HLB symptomatic trees at different times of the year were analyzed to monitor the incidence and spread of HLB. The results showed that spread of ‘Ca. L. asiaticus’ in an area may be detected one to several years before the development of HLB symptoms in plants. The study suggests that discount garden centers and retail nurseries may have played a significant role in the widespread distribution of psyllids and plants carrying HLB pathogens in Florida.

  • distribution and characterization of citrus tristeza virus in south florida following establishment of toxoptera citricida
    Plant Disease, 2004
    Co-Authors: Susan E Halbert, R F Lee, Hanife Genc, Bayram Cevik, Lawrence G Brown, I M Rosales, K L Manjunath, Mark Pomerinke, D A Davison, C L Niblett
    Abstract:

    Halbert, S. E., Genc, H., Cevik, B., Brown, L. G., Rosales, I. M., Manjunath, K. L., Pomerinke, M., Davison, D. A., Lee, R. F., and Niblett, C. L. 2004. Distribution and characterization of Citrus tristeza virus in south Florida following establishment of Toxoptera citricida. Plant Dis. 88:935-941. The incidence of Citrus tristeza virus (CTV) was found to increase significantly in southern Florida within 2 years after the establishment of its most efficient vector, Toxoptera citricida (Kirkaldy). Increased incidence of both mild and severe strains was documented, with the incidence of severe strains increasing more than mild strains. Molecular probes capable of differentiating mild, quick decline and various types of stem-pitting strains demonstrated that trees often were infected with more than one strain of CTV, with trees containing up to five different strains. Some CTV strains detected in the southeast urban corridor of Florida and in commercial groves in southwest Florida were found to react with probes specific for stem-pitting strains known from elsewhere in the world. The implications of the presence of these CTV strains in Florida and their possible presence in citrus budwood scion trees are discussed.

Susan E Halbert - One of the best experts on this subject based on the ideXlab platform.

  • detection of candidatus liberibacter asiaticus in diaphorina citri and its importance in the management of citrus huanglongbing in florida
    Phytopathology, 2008
    Co-Authors: K L Manjunath, Susan E Halbert, Chandrika Ramadugu, Susan E Webb
    Abstract:

    Manjunath, K. L., Halbert, S. E., Ramadugu, C., Webb, S., and Lee, R. F. 2008. Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus huanglongbing in Florida. Phytopathology 98:387-396. Citrus huanglongbing (HLB or citrus greening), is a highly destructive disease that has been spreading in both Florida and Brazil. Its psyllid vector, Diaphorina citri Kuwayama, has spread to Texas and Mexico, thus threatening the future of citrus production elsewhere in mainland North America. Even though sensitive diagnostic methods have been developed for detection of the causal organisms, Candidatus Liberibacter spp., the pathogen cannot be detected consistently in plants until symptoms develop, presumably because of low titer and uneven distribution of the causal bacteria in nonsymptomatic tissues. In the present study, TaqMan based real-time quantitative polymerase chain reaction methodology was developed for detection of ‘Ca. L. asiaticus’ in D. citri. Over 1,200 samples of psyllid adults and nymphs, collected from various locations in Florida, from visually healthy and HLB symptomatic trees at different times of the year were analyzed to monitor the incidence and spread of HLB. The results showed that spread of ‘Ca. L. asiaticus’ in an area may be detected one to several years before the development of HLB symptoms in plants. The study suggests that discount garden centers and retail nurseries may have played a significant role in the widespread distribution of psyllids and plants carrying HLB pathogens in Florida.

  • distribution and characterization of citrus tristeza virus in south florida following establishment of toxoptera citricida
    Plant Disease, 2004
    Co-Authors: Susan E Halbert, R F Lee, Hanife Genc, Bayram Cevik, Lawrence G Brown, I M Rosales, K L Manjunath, Mark Pomerinke, D A Davison, C L Niblett
    Abstract:

    Halbert, S. E., Genc, H., Cevik, B., Brown, L. G., Rosales, I. M., Manjunath, K. L., Pomerinke, M., Davison, D. A., Lee, R. F., and Niblett, C. L. 2004. Distribution and characterization of Citrus tristeza virus in south Florida following establishment of Toxoptera citricida. Plant Dis. 88:935-941. The incidence of Citrus tristeza virus (CTV) was found to increase significantly in southern Florida within 2 years after the establishment of its most efficient vector, Toxoptera citricida (Kirkaldy). Increased incidence of both mild and severe strains was documented, with the incidence of severe strains increasing more than mild strains. Molecular probes capable of differentiating mild, quick decline and various types of stem-pitting strains demonstrated that trees often were infected with more than one strain of CTV, with trees containing up to five different strains. Some CTV strains detected in the southeast urban corridor of Florida and in commercial groves in southwest Florida were found to react with probes specific for stem-pitting strains known from elsewhere in the world. The implications of the presence of these CTV strains in Florida and their possible presence in citrus budwood scion trees are discussed.

Chandrika Ramadugu - One of the best experts on this subject based on the ideXlab platform.

  • detection of candidatus liberibacter asiaticus in diaphorina citri and its importance in the management of citrus huanglongbing in florida
    Phytopathology, 2008
    Co-Authors: K L Manjunath, Susan E Halbert, Chandrika Ramadugu, Susan E Webb
    Abstract:

    Manjunath, K. L., Halbert, S. E., Ramadugu, C., Webb, S., and Lee, R. F. 2008. Detection of ‘Candidatus Liberibacter asiaticus’ in Diaphorina citri and its importance in the management of citrus huanglongbing in Florida. Phytopathology 98:387-396. Citrus huanglongbing (HLB or citrus greening), is a highly destructive disease that has been spreading in both Florida and Brazil. Its psyllid vector, Diaphorina citri Kuwayama, has spread to Texas and Mexico, thus threatening the future of citrus production elsewhere in mainland North America. Even though sensitive diagnostic methods have been developed for detection of the causal organisms, Candidatus Liberibacter spp., the pathogen cannot be detected consistently in plants until symptoms develop, presumably because of low titer and uneven distribution of the causal bacteria in nonsymptomatic tissues. In the present study, TaqMan based real-time quantitative polymerase chain reaction methodology was developed for detection of ‘Ca. L. asiaticus’ in D. citri. Over 1,200 samples of psyllid adults and nymphs, collected from various locations in Florida, from visually healthy and HLB symptomatic trees at different times of the year were analyzed to monitor the incidence and spread of HLB. The results showed that spread of ‘Ca. L. asiaticus’ in an area may be detected one to several years before the development of HLB symptoms in plants. The study suggests that discount garden centers and retail nurseries may have played a significant role in the widespread distribution of psyllids and plants carrying HLB pathogens in Florida.

Da Deng - One of the best experts on this subject based on the ideXlab platform.

  • Combining multiple precision-boosted classifiers for indoor-outdoor scene classification
    'University of Otago Library', 2011
    Co-Authors: Da Deng, Zhang Jianhua
    Abstract:

    Along with the progress of the content-based image retrieval research and the development of the MPEG-7 XM feature descriptors, there has been an increasing research interest on object recognition and semantics extraction from images and videos. In this paper, we revisit an old problem of indoor versus outdoor scene classification. By introducing a precision-boosted combination scheme of multiple classifiers trained on several global and regional feature descriptors, our experiment has led to better results compared with conventional approaches.UnpublishedA.W.M. Smeulders, M. Worring, and S. Santini and A. Gupta, “Content-based Image Retrieval of the end of the early years”. IEEE Trans on PAMI, Vol. 22, No. 12, 2000, pp. 1349-1380. J.M. Corridoni, A.D. Bimbo, and P. Pala, “Image Retrieval by Colour Semantics”, Multimedia System, Vol. 7, No. 3, 1999, pp.175-183. B.S. Manjunath, J. Ohm and V. Vinod, “Colour and Texture Descriptors”, IEEE Trans on Circuits and Systems for Video Technology, Vol. 11, No. 6, 2001, pp.703-715. M. Bober, “MPEG-7 Visual Shape Descriptors”, IEEE Trans. on Circuits and Systems for Video Technology, Vol. 11, 2001, pp.716-719. M. Szummer and R.W. Picard,“Indoor-Outdoor Image Classification,” in Proc. IEEE International Workshop on Content-based Access of Image and Video Databases, 1998, pp.42-51. M. Soysal and A.A. Alatan, “Combining MPEG-7 Based Visual Experts For Reaching Semantics”, in Proc. of VLBV03, Madrid, 2003. J. Li and J.Z. Wang, “Automatic Linguistic Indexing of Pictures by A Statistical Modelling Approach”, IEEE Trans. on PAMI, vol. 25, No. 9, 2003, pp.1075-1088. MPEG-7 eXperimentation Model (XM), Institute for Integrated Systems, Munich University of Technology, Germany. URL http://www.lis.ei.tum.de/research/bv/topics/mmdb/e mpeg7.html. Y. Deng and B.S. Manjunath, “Unsupervised segmentation of colour-texture regions in images and video”, IEEE Trans. on PAMI, Vol. 23, 2001, pp.800-810. J. Kittler, Mohamad Hatef et al., “On Combination Classifiers”, IEEE Trans on PAMI, Vol. 20, No. 3, 1998, pp.226-238

  • Image saliency mapping and ranking using an extensible visual attention model based on MPEG-7 feature descriptors
    'University of Otago Library', 2011
    Co-Authors: Wolf Heiko, Da Deng
    Abstract:

    In visual perception, finding regions of interest in a scene is very important in the carrying out visual tasks. Recently there have been a number of works proposing saliency detectors and visual attention models. In this paper, we propose an extensible visual attention framework based on MPEG-7 descriptors. Hotspots in an image are detected from the combined saliency map obtained from multiple feature maps of multi-scales. The saliency concept is then further extended and we propose a saliency index for the ranking of images on their interestingness. Simulations on hotspots detection and automatic image ranking are conducted and statistically tested with a user test. Results show that our method captures more important regions of interest and the automatic ranking positively agrees to user rankings.UnpublishedL. Itti and C. Koch. Computational modelling of visual attention. Nature Reviews Neuroscience, 2(3):194–203, March 2001. T. Kadir and M. Brady. Saliency, scale and image description. International Journal of Computer Vision, 45(2):83–105, 2001. W.D. Ferreira and D.L. Borges. Detecting and ranking saliency for scene description. In Lecture Notes in Computer Science, volume 3287, pages 76–83, 2004. L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11):1254–1259, November 1998. Y.F. Ma, L. Lu, H.J. Zhang, and M.J. Li. A user attention model for video summarization. In MULTIMEDIA ’02: Proceedings of the tenth ACM international conference on Multimedia, pages 533–542, Juan-les-Pins, France, 2002. A. Smeulders, M. Worring, S. Santini, A. Gupta, and Jain R. Contentbased image retrieval at the end of the early years. IEEE Transaction on Pattern Analysis and Machine Intelligence, 22(12):1349–1380, 2000. B.S. Manjunath, J.-R. Ohm, and V.V. Vasudevan. MPEG-7 color and texture descriptors. IEEE Trans. Circuits Syst. Video Technol., 11:703– 715, June 2001. L. Wang and B.S. Manjunath. A semantic representation for image retrieval. In Proc. ICIP 2003. IEEE, 2003. J. Luo and A. Singhal. On measuring low-level saliency in photographic images. In Proc. IEEE Conf. on CVPR, pages 1084–1089, 2000. F.W.M. Stentiford. An evolutionary programming approach to the simulation of visual attention. In Proc. IEEE Congress on Evolutionary Computation, pages 851–858, 2001. E. Celaya and P. Jim´enez. Salience detection in time-evolving image sequences. In Design and Application of Hybrid Intelligent Systems, pages 852–860, Amsterdam, The Netherlands, 2003. IOS Press. Y.F. Ma and H.J. Zhang. Contrast-based image attention analysis by using fuzzy growing. In MULTIMEDIA ’03: Proceedings of the eleventh ACM international conference on Multimedia, pages 374–381, Berkeley, CA, USA, 2003. Silvia Corchs, Martin Stetter, and Gustavo Deco. Systems-level neuronal modeling of visual attentional mechanisms. Artif. Intell. Rev., 20:143–160, 2003. R. Castano, K. Wagstaff, L. Song, and R.C. Anderson. Validating rover image prioritizations. The Interplanetary Network Progress Report, 42(160), February 2005. D. Deng and H. Wolf. POISE - Achieving content-based picture organisation for image search engines. In Lecture Notes in Computer Science, volume 3682, pages 1–7, August 2005. H. Liu, X. Xie, X. Tang, Z.-W. Li, and W.-Y. Ma. Effective browsing of web image search results. In MIR ’04: Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval, pages 84–90, New York, NY, USA, 2004. B.S. Manjunath, P. Salembier, and T. Sikora, editors. Introduction to MPEG-7: Multimedia Content Description Interface. John Wiley & Sons, Inc., New York, NY, USA, 2002. L. Itti and C. Koch. Comparison of feature combination strategies for saliency-based visual attention systems. In Proc. SPIE Vol. 3644, Human Vision and Electronic Imaging IV, pages 473–482, May 1999. TU Munich. Mpeg-7 experimentation model website. URL http://www.lis.e-technik.tu-muenchen.de/research/bv/topics/mmdb/ e mpeg7.html, 2005. Retrieved 30 October 2005. University of Otago. Photos of the ISB. URL http://www.library.otago.ac.nz/admin/photos.html. Retrieved 30 October 2005. anon. iLab image databases. URL http://ilab.usc.edu/imgdbs. Retrieved 30 October 2005. L. Itti. The iLab Neuromorphic Vision C++ Toolkit: Free tools for the next generation of vision algorithms. The Neuromorphic Engineer, 1(1):10, March 2004. E.L. Lehmann. Nonparametrics: Statistical Methods Based on Ranks. Holden-Day, Inc., San Francisco, CA, USA, 1975. R.E. Quandt. Measurement and inference in wine tasting. In Meetings of the Vineyard Data Quantification Society, Corsica, 1 - 3 October 1998. J.J. Higgins. Introduction to modern nonparametric statistics. Brooks/Cole, Pacific Grove, CA, USA, 2004. S.J. Luck and E.K. Vogel. The capacity of visual working memory for features and conjunctions. Nature, 390:279–281, 20 November 1997. E.K. Vogel and M.G. Machizawa. Neural activity predicts individual differences in visual working memory capacity. Nature, 428:748–751, 15 April 2004

  • Content-based image collection summarization and comparison using self-organizing maps
    'University of Otago Library', 2011
    Co-Authors: Da Deng
    Abstract:

    Progresses made on content-based image retrieval has reactivated the research on image analysis and similarity-based approaches have been investigated to assess the similarity between images. In this paper, the content-based approach is extended towards the problem of image collection summarization and comparison. For these purposes we propose to carry out clustering analysis on visual features using self-organizing maps, and then evaluate their similarity using a few dissimilarity measures implemented on the feature maps. The effectiveness of these dissimilarity measures is then examined with an empirical study.UnpublishedC. Carson, M. Thomas, S. Belongie, et al., Blobworld: A system for region-based image indexing and retrieval, in: Proc. Int. Conf. Visual Inf. Sys., 1999, pp. 509–516. J. Smith, S. Chang, Visualseek: a fully automated content-based image query system, in: Proc. of ACM Multimedia 96, 1996, pp. 87–98. A. Smeulders, M. Worring, S. Santini, A. Gupta, J. R., Content-based image retrieval at the end of the early years, IEEE Transaction on Pattern Analysis and Machine Intelligence 22 (12) (2000) 1349–1380. B. Manjunath, J. Ohm, V. Vinod, A. Yamada, Color and texture descriptors, IEEE Trans. Circuits and Systems for Video Technology Special Issue on MPEG-7. M. Bober, Mpeg-7 visual shape descriptors, IEEE Trans. on Circuits and Systems for Video Technology 11. R. Brunelli, O. Mich, Histograms analysis for image retrieval, Pattern Recognition 34 (2001) 1625–1637. Y. Rubner, C. Tomasi, L. Guibas, A metric for distributions with applications to image databases, in: Proc. of IEEE ICCV, 1998, pp. 59–66. J. R. Mathiassen, A. Skavhaug, K. Bø, Texture similarity measure using kullback-leibler divergence between gamma distributions, in: ECCV ’02: Proceedings of the 7th European Conference on Computer Vision-Part III, Springer-Verlag, London, UK, 2002, pp. 133–147. T. Kohonen, Self-organizing Maps, 2nd Edition, Springer-Verlag, 1997. A. Rauber, D. Merkl, The somlib digital library system, in: Proc. of European Conference on Digital Libraries, 1999, pp. 323–342. J. Laaksonen, M. Koskela, E. Oja, Content-based image retrieval using self-organizing maps, in: Visual Information and Information Systems, 1999, pp. 541–548. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd Edition, Prentice Hall, 1999. H. Ritter, Asymptotic level density for a class of vector quantization processes, IEEE Trans. Neural Networks 2 (1991) 173–175. H. Yin, N. Allison, Self-organizing mixture networks for probability density estimation, IEEE Trans. on Neural Networks 12 (2) (2001) 405–411. W. Sammon, A nonlinear mapping for data analysis, IEEE Trans. on Computers 5 (1969) 401409. S. Kaski, K. Lagus, Comparing self-organizing maps, in: J. Vorbruggen, B. Sendhoff (Eds.), Proceedings of ICANN96 International Conference on Artificial Neural Networks, Vol. 1112 of Lecture Notes in Computer Science, Springer, Berlin, 1996, pp. 809 – 814. T. Honkela, Comparisons of self-organized word category maps, in: Proceedings of WSOM97, Workshop on Self-Organizing Maps, Helsinki University of Technology, Neural Networks Research Centre, Espoo, Finland, 1997, pp. 298–303. B. Fritzke, A growing neural gas network learns topologies, in: Proc. of NIPS, 1994. T. Eiter, H. Mannila, Distance measures for point sets and their computation, Acta Informica 34 (1997) 109–133. B. S. Manjunath, W. Ma, Texture features for browsing and retrieval of image data, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI - Special issue on Digital Libraries) 18 (8) (1996) 837–42. URL http://vision.ece.ucsb.edu/publications/96PAMITrans.pdf T. Kohonen, J. Hynninen, J. Kangas, J. Laaksonen, Som pak: The self-organizing map program package (1996). J. Puzicha, Y. Rubner, C. Tomasi, J. Buhmann, Empirical evaluation of dissimilarity measures for color and texture, in: Proceedings the IEEE International Conference on Computer Vision(ICCV-1999), 1999, pp. 1165–1173. D. Deng, N. Kasabov, On-line pattern analysis by evolving self-organizing maps, Neurocomputing 51 (2003) 87–103. P. Tino, I. Nabney, Hierarchical GTM: Constructing localized nonlinear projection manifolds in a principled way, IEEE Trans. Pattern Anal. Mach. Intell. 24 (5) (2002) 639–656

  • How interesting is this? Finding interest hotspots and ranking images using an MPEG-7 visual attention model
    2011
    Co-Authors: Wolf Heiko, Da Deng
    Abstract:

    A lively Dunedin street scene, and a panoramic view of the Southern Alps - two images that might appeal and interest a viewer. But where do people look, and which of those images appears more interesting? In this paper, we are introducing a visual attention model based on MPEG-7 descriptors that creates multi-scale feature maps to detect interest hotspots in images. Further, we are assessing three methods that use attention models for image ranking and compare them to results gathered in a user test. Preliminary results indicate that rankings created by our model show a high agreement with rankings obtained in a pilot user study.PublishedNon Peer ReviewedCastano, R., Wagstaff, K., Song, L. & Anderson, R. C. (2005). “Validating Rover Image Prioritizations.” The Interplanetary Network Progress Report. 42(160). Celaya, E. & Jim´enez, P. (2003). “Salience detection in time-evolving image sequences.” Design and Application of Hybrid Intelligent Systems. IOS Press Amsterdam, The Netherlands pp. 852–860. Deng, D. & Wolf, H. (2005). “POISE - Achieving content-based picture organisation for image search engines.” Lecture Notes in Computer Science. Vol. 3682. pp. 1–7. Ferreira, W. D. & Borges, D. L. (2004). “Detecting and Ranking Saliency for Scene Description.” Lecture Notes in Computer Science. Vol. 3287. pp. 76–83. iLab Image Databases (2005). Retrieved 30 October 2005. [http://ilab.usc.edu/imgdbs] Itti, L. (2004). “The iLab Neuromorphic Vision C++ Toolkit: Free tools for the next generation of vision algorithms.” The Neuromorphic Engineer. 1(1): 10. Itti, L. & Koch, C. (1999). “Comparison of feature combination strategies for saliency-based visual attention systems.” Proc. SPIE Vol. 3644, Human Vision and Electronic Imaging IV. pp. 473–482. Itti, L. & Koch, C. (2001). “Computational modelling of visual attention.” Nature Reviews Neuroscience. 2(3): 194–203. Itti, L., Koch, C. & Niebur, E. (1998). “A Model of Saliency-Based Visual Attention for Rapid Scene Analysis.” IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(11): 1254–1259. Kadir, T. & Brady,M. (2001). “Saliency, Scale and Image Description.” International Journal of Computer Vision. 45(2): 83–105. Koprinska, I., Clark, J. & Carrato, S. (2004). “VideoGCS - a clustering-based system for video summarization and browsing.” 6th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication. Thessaloniki, Greece pp. 34–40. Koskela, J., Laaksonen, J. & Oja, E. (2001). “Self-organizing image retrieval with MPEG-7 descriptors.” Proceedings of Infotech Oulu International Conference on Information Retrieval (IR’2001). Oulu, Finland. Lehmann, E. (ed.) (1975). Nonparametrics: Statistical Methods Based on Ranks. Holden-Day, Inc. San Francisco, CA, USA. Liu, H., Xie, X., Tang, X., Li, Z.-W. & Ma, W.-Y. (2004). “Effective browsing of web image search results.” MIR ’04: Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval. New York, NY, USA pp. 84–90. Ma, Y., Lu, L., Zhang, H. & Li, M. (2002). “A User Attention Model for Video Summarization.” MULTIMEDIA ’02: Proceedings of the tenth ACM international conference on Multimedia. Juan-les-Pins, France pp. 533– 542. Ma, Y. & Zhang, H. (2003). “Contrast-based image attention analysis by using fuzzy growing.” MULTIMEDIA ’03: Proceedings of the eleventh ACMinternational conference on Multimedia. Berkeley, CA, USA pp. 374– 381. Manjunath, B., Salembier, P. & Sikora, T. (eds) (2002). Introduction to MPEG-7: Multimedia Content Description Interface. John Wiley & Sons, Inc. New York, NY, USA. Martinez, J. M. (2004). “Overview of the MPEG-7 standard.” ISO/IEC JTC1/SC29/WCll N4509. [http://www.chiariglione.org/mpeg/standards/mpeg-7/mpeg-7.htm] Saberi, M., Carrato, S., Koprinska, I. & Clark, J. (2005). “Estimation of the hierarchical structure of a video sequence using MPEG-7 descriptors and GCS.” 9th International Conference on Knowledge-based Intelligent Information & Engineering Systems 2005, Special Session on Machine Learning Techniques for Image and Video Processing. Sydney, Australia. TU Munich (2005). “MPEG-7 experimentation model website.” Retrieved 30 October 2005. [http://www.lis.e-technik.tu-muenchen.de/research/bv/topics/mmdb/e mpeg7.html] University of Otago (2005). “Photos of the ISB.” Retrieved 30 October 2005. [http://www.library.otago.ac.nz/admin/photos.html] Wolf, H. (2005). “Automatic video summary using a visual attention model.” Otago University Student’s Association Postgraduate Symposium. Dunedin, New Zealand. [http://www.covic.otago.ac.nz/˜hwolf/pubs/wolf posterOUSA.pdf