Have a personal or library account? Click to login
Time-Varying-Geometry Object Surveillance Using A Multi-Camera Active-Vision System Cover

Time-Varying-Geometry Object Surveillance Using A Multi-Camera Active-Vision System

Open Access
|Dec 2017

References

  1. 1K.A. Tarabanis, P.K. Allen, and R.Y. Tsai, “A Survey of Sensor Planning in Computer Vision,” IEEE Transactions on Robotics and Automation, vol. 11, no. 1, pp 86–104, Feb. 1995.10.1109/70.345940
  2. 2J. Miura and K. Ikeuchi, “Task-Oriented Generation of Visual Sensing Strategies in Assembly Tasks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 2, pp. 126-138, Feb. 1998.10.1109/34.659931
  3. 3M.D. Naish, E.A. Croft, and B. Benhabib, “Coordinated Dispatching of Proximity Sensors for the Surveillance of Maneuvering Targets,” Journal of Robotics and Computer Integrated Manufacturing, Vol. 19, No. 3, pp. 283-299, 2003.10.1016/S0736-5845(02)00085-6
  4. 4S. Sakane, T. Sato, and M. Kakikura, “Model-Based Planning of Visual Sensors Using a Hand-Eye Action Simulator: HEAVEN,” Proc. of Conf. on Advanced Robotics, pp. 163–174, Versailles, France, Oct. 1987.10.1163/156855387X00138
  5. 5C.K. Cowan and P.D. Kovesik, “Automated Sensor Placement for Vision Task Requirements,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 3, pp. 407-416, May 1988.10.1109/34.3905
  6. 6R. Bodor, P. Schrater, and N. Papanikolopoulos, “Multi-Camera Positioning to Optimize Task Observability,” Proc. of IEEE Conf. on Advanced Video and Signal Based Surveillance, pp. 552-557, 2005.
  7. 7S. Yu, D. Tan, and T. Tan, “A Framework for Evaluating the Effect of View Angle, Clothing, and Carrying Condition on Gait Recognition,” Proc. of Int. Conf. on Pattern Recognition, pp. 441-444, Hong Kong, 2006.
  8. 8L. Hodge and M. Kamel, “An Agent-Based Approach to Multi-sensor Coordination,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, vol. 33, no. 5, pp. 648-662, Sept. 2003.10.1109/TSMCA.2003.817397
  9. 9D.P Anderson, “Efficient Algorithms for Automatic Viewer Orientation,” Comp. & Graphics, vol. 9, no. 4, pp. 407-413, 1985.10.1016/0097-8493(85)90035-4
  10. 10S. Sakane, T. Sato, and M. Kakikura, “Model-Based Planning of Visual Sensors Using a Hand-Eye Action Simulator: HEAVEN,” Proc. of Conf. on Advanced Robotics, pp. 163174, Versailles, France, Oct. 1987.
  11. 11C.K. Cowan and P.D. Kovesik, “Automated Sensor Placement from Vision Task Requirements,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 3, pp. 407-416, May 1988.10.1109/34.3905
  12. 12D.P Anderson, “Efficient Algorithms for Automatic Viewer Orientation,” Comp. & Graphics, vol. 9, no. 4, pp. 407-413, 1985.10.1016/0097-8493(85)90035-4
  13. 13M.K. Reed and P.K. Allen, “Constraint-Based Sensor Planning for Scene Modeling,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 12, pp. 1460-1467, Dec. 2000.
  14. 14L. Hodge and M. Kamel, “An Agent-Based Approach to Multi-sensor Coordination,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, vol. 33, no. 5, pp. 648-662, Sept. 2003.10.1109/TSMCA.2003.817397
  15. 15T. Urano, T. Matsui, T. Nakata, and H. Mizoguchi, “Human Pose Recognition by Memory-Based Hierarchical Feature Matching,” Proc. of IEEE International Conference on Systems, Man, and Cybernetics, pp. 6412-6416, The Hague, Netherlands, 2004.
  16. 16M.D. Naish, E.A. Croft, and B. Benhabib, “Coordinated Dispatching of Proximity Sensors for the Surveillance of Maneuvering Targets,” Journal of Robotics and Computer Integrated Manufacturing, vol. 19, no. 3, pp. 283-299, 2003.10.1016/S0736-5845(02)00085-6
  17. 17R. Murrieta-Cid, B. Tovar, and S. Hutchinson, “A Sampling-Based Motion Planning Approach to Maintain Visibility of Unpredictable Targets,” Journal of Autonomous Robots, vol. 19, no. 3, pp. 285-300, 2005.10.1007/s10514-005-4052-0
  18. 18J. R. Spletzer, and C. J Taylor, “Dynamic Sensor Planning and Control for Optimally Tracking Targets,” Int. Journal of Robotic Research, vol. 22, no. 1, pp. 7-20, Jan. 2003.10.1177/0278364903022001002
  19. 19M. Kamel, and L. Hodge, “A Coordination Mechanism for Model-Based Multi-Sensor Planning,” Proc. of the IEEE International Symposium on Intelligent Control, pp. 709714, Vancouver, Oct. 2002
  20. 20J. Spletzer and C. J. Taylor, “Sensor Planning and Control in a Dynamic Environment,” Proc. of IEEE Int. Conf. Robotics and Automationpp. 676–681, Washington, DC, 2002.
  21. 21S.G. Goodridge, R.C. Luo, and M.G. Kay, “Multi-Layered Fuzzy Behavior Fusion for Real-Time Control of Systems with Many Sensors,” IEEE Transactions on Industrial Electronics, vol. 43, no. 3, pp. 387-394, 1996.10.1109/41.499811
  22. 22S. G. Goodridge and M. G. Kay, “Multimedia Sensor Fusion for Intelligent Camera Control,” Proc of IEEE/SICE/RSJ Multi-sensor Fusion and Integration for Intelligent Systems, pp. 655-662, Washington, DC, Dec. 1996.
  23. 23A. Bakhtari, and B. Benhabib, “An Active Vision System for Multi-Target Surveillance in Dynamic Environments,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 37, no. 1, pp. 190-198, 2007.10.1109/TSMCB.2006.88342317278571
  24. 24E. Marchand and F. Chaumette, “Active Vision for Complete Scene Reconstruction and Exploration,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 1, pp. 65-72, Jan. 1999.10.1109/34.745736
  25. 25R. Pito, “A Solution to the Next Best View Problem for Automated Surface Acquisition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 10, pp. 1016-1030, Oct. 1999.
  26. 26S.D. Roy, S. Chaudhury, and S. Banerjee, “Isolated 3-D Object Recognition through Next View Planning,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, vol. 30, no. 1, pp. 67-76, Jan. 2000.10.1109/3468.823482
  27. 27J.E. Banta, L.M. Wong, C. Dumont, and M.A. Abidi, “A Next-Best-View System for Autonomous 3-D Object Reconstruction,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, vol. 30, no. 5, pp. 589-598, Sept. 2000.10.1109/3468.867866
  28. 28S.Y. Chen and Y.F. Li, “Vision Sensor Planning for 3-D Model Acquisition,” IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics, vol. 35, no. 5, pp. 894-904, Oct. 2005.10.1109/TSMCB.2005.846907
  29. 29G. Johansson, “Visual Perception of Biological Motion and a Model for its Analysis,” Percept. Psychophys., vol. 14, no. 2, pp. 201-211, 1973.10.3758/BF03212378
  30. 30R. Chellappa, A.K. Roy-Chowdhury, and S K. Zhou, “Recognition of Humans and Their Activities Using Video,” San Rafael, CA: Morgan & Claypool Pub., pp. 53-92, 2005.10.1007/978-3-031-02236-4_3
  31. 31J.E. Cutting and L.T. Kozlowski, “Recognizing Friends by Their Walk: Gait Perception without Familiarity Cues,” Bull. Psychonom. Soc., vol. 9, no. 5, pp. 353-356, 1977.10.3758/BF03337021
  32. 32A. Kale, A.K. Roy-Chowdhury, and R. Chellappa, “Fusion of Gait and Face for Human Identification,” Proc. of ICASSP04, pp. 901-904, Montreal, Canada, 2004.
  33. 33H. Kobayashi and F. Hara, “Facial Interaction between Animated 3D Face Robot and Human Beings,” Proc. of IEEE Int. Conf. on Computational Cybernetics and Simulation, pp. 3732-3737, Orlando, FL, 1997.
  34. 34M. Dimitrijevic, V. Lepetit and P. Fua, “Human Body Pose Recognition Using SpatioTemporal Templates,” ICCV workshop on Modeling People and Human Interaction, pp. 127-139, Beijing, China, October 2005.10.1016/j.cviu.2006.07.007
  35. 35D. Cunado, M. S. Nixon, and J. Carter, “Automatic Extraction and Description of Human Gait Models for Recognition Purposes,” Computer Vision and Image Understanding, vol. 90, pp. 1-41, 2003.10.1016/S1077-3142(03)00008-0
  36. 36G. V. Veres, L. Gordon, J. N. Carter, and M.S. Nixon, “What Image Information is Important in Silhouette-Based Gait Recognition?” Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, pp. 776-782, Washington, D.C., 2004.
  37. 37X. Weimin, L. Ying, H, Hongzhe, X. Lun, W. Zhiliang, and C. Fengjun, “New Approach of Gait Recognition for Human ID,” Proc. of ICSP04, pp. 199-202, Beijing, China, 2004.
  38. 38N. Rajpoot and K. Masood, “Human Gait Recognition with 3D Wavelets and Kernel based Subspace Projections,” Proc. of Workshop on Human Activity Recognition and Modeling, HAREM 2005, Oxford, UK, 2005.
  39. 39D. Xu, S. Yan, D. Tao, L. Zhang, X. Li, and H. Zhang. “Human Gait Recognition with Matrix Representation,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no. 7, pp. 896-903, July 2006.10.1109/TCSVT.2006.877418
  40. 40R. Kalman, “A New Approach to Linear Filtering and Prediction Problems,” Journal of Basic Engineering, pp. 35-45, March 1960.10.1115/1.3662552
  41. 41D.G. Lowe, “Object Recognition from Local Scale-Invariant Features,” Proc. of IEEE Int’l Conf. on Computer Vision, Kerkyra, Greece, pp. 1150-1157 1999.10.1109/ICCV.1999.790410
  42. 42H. Jing, C. K. Fi, and E.C. Prakash, “Component Based Human Animation Architecture – Design Issues,” Proc. of TENCON, vol. 2, pp. 528-532, Kuala Lumpur, 2000.
  43. 43J. D. Shutler, M. G. Grant, M. S. Nixon, and J. N. Carter, “On a Large Sequence-Based Human Gait Database,” Proc. of 4th International Conference on Recent Advances in Soft Computing, pp. 66-72, Nottingham UK, 2002.
Language: English
Page range: 679 - 704
Published on: Dec 13, 2017
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2017 Matthew Mackay, Robert G. Fenton, Beno Benhabib, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.