DYNAMIC EVENT INTERPRETATION AND DESCRIPTION FROM VISUAL SCENE BASED ON COGNITIVE ONTOLOGY FOR RECOGNITION BY A ROBOT

Y. Wakuda, K. Sekiyama, and T. Fukuda

References

  1. [1] Y. Zhai & M. Shah, Video scene segmentation using Markovchain Monte Carlo, IEEE Transactions on Multimedia, 8(4),2006, 686–697.
  2. [2] R.J. Radke, S. Andra, O. Al-Kofahi, & B. Roysam, Im-age change detection algorithms: A systematic survey, IEEETransactions on Image Processing, 14(3), 2005, 294–307.
  3. [3] A.R.-Acha, Y. Pritch, & S. Peleg, Making a long video short:dynamic video synopsis, Proceedings on Computer Vision andPattern Recognition, 2006 IEEE Computer Society Conference(CVPR), 1, 2006, 435–441.
  4. [4] S. Hongeng, R. Nevatia, & F. Bremond, Video-based eventrecognition: Activity representation and probabilistic recog-nition methods, Computer Vision and Image Understanding,96(2), 2004, 129–162.
  5. [5] F. Cheng, W.J. Christmas, & J. Kittler, Detection and de-scription of human running behaviour in sportsvideo multi-media database, Proc. 11th Int. Conf. on Image Analysis andProcessing, 2001, 366–371.
  6. [6] C.-W. Ngo, T.-C. Pong, & H.-J. Zhang, On clustering andretrieval of video shots through temporal slices analysis, IEEETransactions on Multimedia, 4(4), 2002, 446–458.
  7. [7] X. Tong, L. Duan, C. Xu, Q. Tian, & H. Lu, Local motionanalysis and its application in video based swimming stylerecognition, 18th Int. Conf. on Pattern Recognition (ICPR’06),Hong Kong, 2, 2006, 1258–1261.
  8. [8] R.T. Collins et al., A system for video surveillance and monitor-ing: VSAM final report, Technical Report CMU-RI-TR-00-12,Carnegie Mellon University, 2000.
  9. [9] L. Wang, W. Hu, & T. Tan, Recent developments in humanmotion analysis, Pattern Recognition, Published by ElsevierScience B.V., 36(3), 2003, 585–601.
  10. [10] X. Yu & S.X. Yang, A study of motion recognition from videosequences, Computing and visualization in science archive,8(1), 2005, 19–25.
  11. [11] K. Makio, Y. Tanaka, & K. Uehara, Discovery of Skills fromMotion Data New Frontiers in Artificial Intelligence: JSAI2003 and JSAI 2004 Conferences and Workshops, LNAI, 3609,2007, 266–282.
  12. [12] R. Cutler & L.S. Davis, Robust real-time periodic motiondetection, analysis, and applications, IEEE Transactions onPattern Analysis and Machine Intelligence, 22(8), 2000, 781–796.
  13. [13] A. Mohan, C. Papageorgiou, & T. Poggio, Example-basedobject detection in images by components, IEEE Transactionson Pattern Recognition and Machine Intelligence, 23(4), 2001,349–361.
  14. [14] L. Zhao & C. Thorpe, Recursive context reasoning for humandetection and parts identification, Proc. of IEEE Workshopon Human Modeling, Analysis and Synthesis, 2000.
  15. [15] G. Chen & D. Kotz, A survey of context-aware mobile comput-ing research, Dartmouth Computer Science Technical ReportTR2000-381, 2000.
  16. [16] J.C.S. Jacques Jr., A.A. Braun, J. Soldera, S.R. Musse, et al.,Understanding people motion in video sequences using Voronoidiagrams, Pattern Analysis & Applications, 10(4), 2007.
  17. [17] L.B.S.L. Jones, J.F. Gareth, A.F. Smeaton, Video semanticcontent analysis based on ontology, Machine Vision and ImageProcessing Conference, 2007. IMVIP 2007. International, 2007,117–124.
  18. [18] Y. Dedeoglu, B.U. Toreyin, U. Gudukbay, & A.E. Cetin, Real-time fire and flame detection in video, Proceedings of IEEEInternational Conference on Acoustics, Speech, and SignalProcessing, 2, 2005, 669–672.
  19. [19] J.C.S. Jacques Jr., A. Braun, J. Soldera, S.R. Musse, et al.,Understanding people motion in video sequences using Voronoidiagrams: Detecting and classifying groups, Pattern Analysis& Applications archive, 10(4), 2007, 321–332.278
  20. [20] K. Andreas, K. Matthias, S. Thomas, M. Mrinal, et al., Motion-based object segmentation using sprites and anisotropic diffu-sion, Eighth Int. Workshop on Image Analysis for MultimediaInteractive Services 2007, 35.
  21. [21] P. Cavanagh, A.T. Labianca, & I.M. Thornton, Attention-based visual routines: sprites, Cognition, 80, 2001, 47–60.
  22. [22] J.K. Tsotsos, S.M. Culhane, W.Y.K. Wai, Y.Lai, et al., Model-ing visual attention via selective tuning, Artificial Intelligence,78(1–2), 1995, 507–545.
  23. [23] L. Itti, C. Koch, & E. Niebur, A Model of saliency-based visualattention for rapid scene analysis, Transactions on PatternAnalysis and Machine Intelligence, (TPAMI), 20(11), 1998,1254–1259.
  24. [24] L. Itti & C. Koch, Computational modelling of visual attention,Nature Reviews: Neuroscience, 2001, 194–203.
  25. [25] L. Steels & J.C. Baillie, Shared grounding of event descriptionsby autonomous robots, Robotics and Autonomous Systems,43(2–3), 2003, 163–173.
  26. [26] Y. Demiris & B. Khadhouri, Hierarchical attentive multiplemodels for execution and recognition of actions, Robotics andAutonomous Systems, 54(5), 2006, 361–369.
  27. [27] D. Walther, U. Rutishauser, C. Koch, & P. Perona, Selectivevisual attention enables learning and recognition of multi-ple objects in cluttered scenes, Computer Vision and ImageUnderstanding, 100(1–2), 2005, 41–63.
  28. [28] P. John, Biopsychology, Fifth Edition, (Boston & New York:Pearson, 2005).
  29. [29] J. Sowa, Distinction, combination, and constraints, Proc. ofIJCAI-95 Workshop on Basic Ontological Issues in KnowledgeSharing, 1995.
  30. [30] A.C. Rosen, S.M. Rao, P. Caffarra, A. Scaglioni, et al.,Neural basis of endogenous and exogenous spatial orienting:A functional MRI Study, Journal of Cognitive Neuroscience,11(2), 1999, 135–152.
  31. [31] I. Haritaoglu, D. Harwood, & L.S. Davis, W4: real-timesurveillance of people and their activities, IEEE Transactionson Pattern Analysis and Machine Intelligence, 22(8), 2000,809–830.
  32. [32] H.M. Lakany, G.M. Haycs, M.E. Hazlewood, & S.J. Hillman,Human walking: Tracking and analysis, Proc. of IEE Col-loquium on Motion Analysis and Tracking, London, 1999,5/1–5/14.
  33. [33] D. Meyer, J. Denzler, & H. Niemann, Model based extractionof articulated objects in image sequences for gait analysis.Proc. of IEEE Intl. Conf. on Image Processing, 1997, 78–81.
  34. [34] E. Sato & T. Yamaguchi, Human to robots communicationusing ontological network system, International Journal ofInnovative Computing, Information and Control ICIC Inter-national, 2(1), 2006.

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