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Applications

  • Ester Martínez-Martín
  • Ángel P. del Pobil
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

Motion detection is of widespread interest due to a large number of applications in various disciplines such as, for instance, video surveillance [1, 2, 3, 4], remote sensing [5, 6, 7, 8], medical diagnosis and treatment [9, 10, 11], civil infrastructure [12, 13, 14], underwater sensing [15, 16, 17], objective measures of intervention effectiveness in team sports [18], and driver assistance system [19, 20, 21], to name some. Among the diversity, some real applications have been implemented to evaluate approach’s performance. These real applications as well as their performance results are presented and discussed through this chapter.

Keywords

Machine vision Computer vision Image segmentation Background subtraction Motion detection Robot vision Dynamic environments Visual surveillance Applications Real applications Human behavior analysis Visual activity monitoring 

References

  1. 1.
    Kiryati, N., Raviv, T., Ivanchenko, Y., Rochel, S.: Real-time abnormal motion detection in surveillance video. In: The 19th International Conference on Pattern Recognition (ICPR). Tampa, Florida, USA (2008)Google Scholar
  2. 2.
    Abdelkader, M., Chellappa, R., Zheng, Q., Chan, A.: Integrated motion detection and tracking for visual surveillance. In: Fourth IEEE International Conference on Computer Vision Systems (ICVS), p. 28. New York, USA (2006)Google Scholar
  3. 3.
    Stauffer, C., Grimson, W.: Learning patterns of activity using real-time tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 27(5), 747–757 (2000)Google Scholar
  4. 4.
    Wren, C., Azarbeyejani, A., Darrell, T., Pentland, A.: Pfinder: Real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 19(7), 780–785 (1997).Google Scholar
  5. 5.
    Hua, W., Li, P.: Polygon change detection for spot5 color image using multi-feature-clustering-analysis. In: Sixth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 260–263. Tianjin, China (2009)Google Scholar
  6. 6.
    Ramachandra, T., Kumar, U.: Geographic resources decision support system for land use, land cover dynamics analysis. In: FOSS/GRASS Users Conference. Bangkok, Thailand (2004)Google Scholar
  7. 7.
    Prenzel, B., Treitz, P.: Remote sensing of land-cover and land-use change for a complex tropical watershed in north sulawesi, indonesia. Remote Sensing for Mapping Land-Cover and Land-Use Change 61(4), 349–363 (2004)Google Scholar
  8. 8.
    Bruzzone, L., Prieto, D.: An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images. IEEE Transactions on Image Processing 11(4), 452–466 (2002)Google Scholar
  9. 9.
    Seo, H., Milanfar, P.: A non-parametric approach to automatic change detection in mri images of the brain. In: The Sixth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI). Boston, Massachusets, USA (2009)Google Scholar
  10. 10.
    Rousseau, F., Faisan, S., Heitz, F., Armspach, J., Y. Chevalier, F. Blanc, Seze, J., Rumbach, L.: An a contario approach for change detection in 3d multimodal images: Application to multiple sclerosis in mri. IEEE Engineering in Medicine and Biology Society (EMBS) pp. 2069–2072 (2007)Google Scholar
  11. 11.
    Patriarche, J., Erickson, B.: Part 1. automated change detection and characterization in serial mr studies of brain tumor patients. Journal of Digital Imaging 20, 203–222 (2007)Google Scholar
  12. 12.
    Landis, E., Zhang, T., Nagy, E., Nagy, G., Franklin, W.: Cracking, damage and fracture in four dimensions. Materials and Structures 40, 357–364 (2007)Google Scholar
  13. 13.
    Landis, E., Nagy, E., Keane, D.: Microstructure and fracture in three dimensions. Engineering Fracture Mechanics 70, 911–925 (2003)Google Scholar
  14. 14.
    Nagy, G., Zhang, T., Franklin, W., Landis, E., Nagy, E., Keane, D.: Volume and surface area distributions of cracks in concrete. In: IWVF4, Lecture Notes in Computer Science (LNCS) 2059, pp. 759–768. Springer-Verlag Berlin / Heidelberg (2001)Google Scholar
  15. 15.
    Qi, Z., Cooperstock, J.: Automated change detection in an undersea environment using a statistical background model. In: MTS/IEEE Oceans Conference. Vancouver, BC, Canada (2007)Google Scholar
  16. 16.
    Williams, R., Lambert, T., Kelsall, A., Pauly, T.: Detecting marine animals in underwater video: Let’s start with salmon. In: Twelfth Americas Conference on Information Systems, pp. 1482–1490. Acapulco, Mexico (2006)Google Scholar
  17. 17.
    Edgington, D., Salamy, K., Risi, M., Sherlock, R., Walther, D., Christof, K.: Automated event detection in underwater video. In: MTS/IEEE Oceans Conference. San Diego, California (2003)Google Scholar
  18. 18.
    Barris, S., Button, C.: A review of vision-based motion analysis in sport. Sports Medicine 38, 1025–1043 (19) (2008)Google Scholar
  19. 19.
    Fang, C., Chen, C., Cherng, S., Chen, S.: Critical motion detection of nearby moving vehicles in a vision-based driver assistance system. IEEE Transactions on Intelligent Transportation Systems 10, 70–82 (2009)Google Scholar
  20. 20.
    Yen, P., Fang, C., Chen, S.: Motion analysis of nearby vehicles on a freeway. In: IEEE International Conference on Networking, Sensing and Control, vol. 2, pp. 903–908, (2004)Google Scholar
  21. 21.
    Fang, C., Chen, S., Fuh, C.: Automatic change detection of driving environments in a vision-based driver assistance system. IEEE Transactions on Neural Networks 14, 646–657 (2003)Google Scholar
  22. 22.
    Tinbergen, N.: On aims and methods in ethology. Zeitschrift fur Tierpsychologie 20(4), 410–433 (1963)Google Scholar
  23. 23.
  24. 24.
    Atkociunas, E., Blake, R., Juozapavicius, A., Kazimianec, M.: Image processing in road traffic analysis. Nonlinear Analysis: Modelling and Control 10(4), 315–332 (2005)Google Scholar
  25. 25.
    Cheung, S., Kamath, C.: Robust techniques for background subtraction in urban traffic video. Electronic Imaging: Video Communications and Image Processing 5308(1), 881–892 (2004)Google Scholar
  26. 26.
    Kastrinaki, V., Zervakis, M., Kalaitzakis, K.: A survey of video processing techniques for traffic applications. Image and Vision Computing 21(4), 359–381 (2003)Google Scholar
  27. 27.
    Fathy, M., Siyal, M.: A window-based image processing technique for quantitative and qualitative analysis of road traffic parameters. IEEE Transactions on Vehicular Technology 47(4), 1342–1349 (1998)Google Scholar
  28. 28.
  29. 29.
    Seo, H.J., Milanfar, P.: Detection of human actions from a single example. In: IEEE International Conference on Computer Vision (ICCV), pp. 1965–1970. Kyoto (2009)Google Scholar
  30. 30.
    Moeslund, T., Granum, E.: A survey of computer vision-based human motion capture. Computer Vision and Image Understanding (CVIU) - Modeling people toward vision-based understanding of a person’s shape, appearance, and movement 81, 231–268 (2001)Google Scholar
  31. 31.
    Moeslund, T., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding (CVIU) 104, 90–126 (2006)Google Scholar
  32. 32.
    Poppe, R.: Vision-based human motion analysis: An overview. Computer Vision and Image Understanding 108, 4–18 (2007)Google Scholar
  33. 33.
    Turaga, P., Chellappa, R., Subrahmanian, V., Udrea, O.: Machine recognition of human activities: A survey. IEEE Transactions on Circuits and Systems for Video Technology 18, 1473–1488 (2008)Google Scholar
  34. 34.
    Farin, D., Krabbe, S., de With, P., Effelsberg, W.: Robust camera calibration for sport videos using court models. In: SPIE Electronic Imaging, vol. 5307, pp. 80–91. San Jose, CA, USA (2004)Google Scholar
  35. 35.
    Farin, D., Han, J., de With, P.: Fast camera calibration for the analysis of sport sequences. In: IEEE International Conference on Multimedia and Expo (ICME) (2005)Google Scholar
  36. 36.
    Ohta, Y., Kitahara, I., Kameda, Y., Ishikawa, H., Koyama, T.: Live 3d video in soccer stadium. International Journal of Computer Vision 75, 173–187 (2007)Google Scholar
  37. 37.
    Ali, A., Farrally, M.: A computer-video aided time motion analysis technique for match analysis. Sports Medicine and Physical Fitness 13, 82–88 (1991).Google Scholar
  38. 38.
    Erdmann, W.: Gathering of kinematic data of sport event by televising the whole pitch and track. In: 10th International Society of Biomechanics in Sports Symposium (ISBS), pp. 159–162. Milan, Italy (1992)Google Scholar
  39. 39.
    Hill, A.: The physiological basis of athletic records. The Scientific Monthly 21, 409–428 (1925)Google Scholar
  40. 40.
    Keller, J.: Optimal velocity in a race. American Mathematical Monthly 81, 474–480 (1974)Google Scholar
  41. 41.
    Richards, J.: The measurement of human motion: A comparison of commercially available systems. Human Movement Science 18, 589–602 (1999)Google Scholar
  42. 42.
    Pers, J., Vuckovic, G., Kovacic, S., Dezman, B.: A low-cost real-time tracker of live sport events. In: International Symposium of Image and Signal Processing and, Analysis, pp. 362–365 (2001)Google Scholar
  43. 43.
    Vuèkoviè, G., Dezman, B., Erculj, F., Kovacic, S., Pers, J.: Differences between the winning and the losing players in a squash game in terms of distance covered. In: The Eighth International Table Tennis Federation Sports Science Congress and The Third World Congress of Science and Racket Sports, pp. 202–207 (2004)Google Scholar
  44. 44.
    Bon, M., Šibila, M., Pori, P.: Sagit computer vision system for tracking handball players during the match. In: EURO 2004 Coaches’ Seminar during the 2004 Men’s European Championship. Slovenia (2004)Google Scholar
  45. 45.
    Robocup world championship and conference. http://www.robocup.org/ (1997)
  46. 46.
    TeamLeondingMicros: A 3 versus 3 mirosot game between the leonding micros and team austro of the ihrt institute from vienna. http://www.youtube.com/watch?v=QhmehYb2Rtg (2007)

Copyright information

© Ester Martínez-Martín 2012

Authors and Affiliations

  • Ester Martínez-Martín
    • 1
  • Ángel P. del Pobil
    • 1
  1. 1.Department of Computer Science and EngineeringJaume I UniversityCastellón de la PlanaSpain

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