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Prediction-based Object Tracking and Coverage in Visual Sensor Networks

Prediction-based Object Tracking and Coverage in Visual Sensor Networks. Tzung -Shi Chen Jiun-Jie Peng,De -Wei Lee Hua -Wen Tsai Dept. of Com. Sci. and Info. Dept . of Info. and Learning Dept . of Computer Info. and

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Prediction-based Object Tracking and Coverage in Visual Sensor Networks

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  1. Prediction-based Object Tracking and Coverage in Visual Sensor Networks Tzung-Shi Chen Jiun-JiePeng,De-Wei Lee Hua-Wen Tsai Dept. of Com. Sci. and Info. Dept. of Info. and Learning Dept. of Computer Info. and Engineering Technology Network Eng. National University of Tainan National University of Tainan LunghwaUniversity of Science Tainan 700, Taiwan Tainan 700, Taiwan and Technology, Taiwan IEEE Proceedings of The 7th International Wireless Communications and Mobile Computing Conference (IWCMC 2011)

  2. Outline Introduction Goals Network Model and Assumptions Prediction-based algorithm for the tracking and coverage of objects(POTC) Experimental results Conclusion

  3. Introduction 0/1 • Visual sensor networks(VSNs) are a type of wireless sensor network. • All sensor are equipped with cameras • Difference between visual and scalar sensor • Visual sensor can capture the image of object Scalar sensor Visualsensor

  4. Introduction When tracking a mobile object, visual sensors cannot remain in an active mode until the object is out of the sensing range To track objects, a set of visual sensors must be active before the mobile object approaches them

  5. Goals • We have developed an algorithm to monitor the mobile object • Minimum number of visual sensors • Maximum coverage of mobile object

  6. Network Model and Assumptions Mobile object Sensor Node • Each sensor • Deploying randomly • Communication range = Sensing range • Location-aware • Location of object • Equipped the camera • Camera can rotate 360° • Active and sleep • The object is mobile and moving with a random waypoint • Build up a planar graph by Gabriel Graph for the visual sensor network

  7. Prediction-based algorithm for the tracking and coverage of objects(POTC) Awakening the Monitoring Area using Face Routing Covered Range

  8. Prediction-based algorithm for the tracking and coverage of objects(POTC) Awakening the Monitoring Area using Face Routing Covered Range

  9. Prediction-based algorithm for the tracking and coverage of objects(POTC) Mobile object Sensor node Nearest node Cross node Cross edge Moving edge

  10. Prediction-based algorithm for the tracking and coverage of objects(POTC) F5 F6 F3 F1 F4 F2 Mobile object Sensor node Nearest node Cross node Wake node Cross edge Moving edge Routing edge

  11. Prediction-based algorithm for the tracking and coverage of objects(POTC) F11 F9 F10 F7 F8 F5 F6 F3 F1 F4 F2 F17 F16 Mobile object F12 F14 F15 F13 Sensor node Boundary node Wake node Cross edge Moving edge Routing edge

  12. Prediction-based algorithm for the tracking and coverage of objects(POTC) Awakening the Monitoring Area using Face Routing Covered Range

  13. Prediction-based algorithm for the tracking and coverage of objects(POTC) Both Covered Segment Covered Segment • Covered Range • Single Characteristic Point • Multiple Characteristic Point

  14. Prediction-based algorithm for the tracking and coverage of objects(POTC) • Covered Range • Single Characteristic Point • Multiple Characteristic Point

  15. Experimental results

  16. Experimental results

  17. Experimental results

  18. Experimental results

  19. Conclusion • we developed the algorithm, prediction-based objecttracking and coverage algorithm (POTC)to monitor the mobile object • Minimum number of visual sensors • Maximum coverage of mobile object

  20. Thank you

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