Future works

In our system, the moving human can be detected and tracked smoothly and continuously. But there are some situations which will result in tracking lost. For example, the background has significant light changes that will lead to moving human changing its character.

In order to use particle filter with active camera in real-time, we reduces the bins of color histogram and the number of samples, it sometimes affects the accuracy of tracking. It can be solved by using some optimized methods in samples. For example, mean-shift can be used to optimize each sample in particle filter.

The active camera is driven by pelco P protocol and uses PID controller to pan or tilt. The results of driving active camera are successful. But it doesn’t use the result of 𝑣_𝑥 and 𝑣_𝑦 in estimated target state vector 𝑠_{𝑡𝑎𝑟𝑔𝑒𝑡}. The 𝑣_𝑥 and 𝑣_𝑦 can be involved in the speed of pan and tilt to increase the accuracy of camera control.

44

References

[1] W. J. Gillner, “Motion based vehicle detection on motorways”, Proceedings of the IEEE Intelligent Vehicles '95 Symposium, pp. 483-487, September 1995.

[2] P. H. Batavia, D. A. Pomerleau, and C. E. Thorpe, “Overtaking vehicle detection using implicit optical flow”, Proceedings of the IEEE Transportation Systems Conference, pp. 729-734, November 1997.

[3] L. Zhao and C. E. Thorpe, “Stereo- and neural network-based pedestrian detection”, IEEE Transactions on Intelligent Transportation Systems, vol. 1, pp.

148-154, September 2000.

[4] N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886-893, 2005.

[5] S. Montabone, A. Soto, “Human detection using a mobile platform and novel features derived from a visual saliency mechanism”, Image and Vision Computing, vol. 28, pp. 391-402, 2010.

[6] P. Viola, M. J. Jones, and D. Snow, “Detecting Pedestrians Using Patterns of Motion and Appearance”, International Journal of Computer Vision, vol. 63, pp.

153-161, 2005.

[7] M. Dimitrijevic, V. Lepetit, and P. Fua, “Human body pose detection using Bayesian spatio-temporal templates”, Computer Vision and Image Understanding, vol.104, pp.127-139, 2006.

[8] R. C. Gonzalez, R. E. Woods, Digital Image Processing, Addison-Wesley, New York, 1992.

[9] D. Marr and E. Hildreth, “Theory of edge detection”, Proceedings of the Royal Society, vol. 207, pp. 197–217, London, 1980.

[10] W. Guo, D. L. Bi, L. Liu, “Human motion tracking based on shape analysis”, Proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, pp. 2-4, Beijing, China, November 2007.

[11] T. Law, H. Itoh, and H. Seki, “Image filtering, edge detection, and edge tracing using fuzzy reasoning”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, pp. 481-491, May 1996.

[12] O. Williams, A. Blake, and R. Cipolla, “Sparse bayesian learning for efficient visual tracking”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, pp. 1292–1304, August 2005.

[13] A. Agarwal and B. Triggs, “Recovering 3D human pose from monocular images”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, pp.

45

44-58, January 2006.

[14] B. Han and L. Davis, “Object tracking by adaptive feature extraction”, International Conference on Image Processing, pp. 1501-1504, October 2004.

[15] R. T. Collins, Y. Liu and M. Leordeanu, “Online selection of discriminative tracking features”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, pp.1631-1643, October 2005.

[16] K. Fukunaga and L. D. Hostetler, “The estimation of the gradient of a density function, with applications in pattern recognition”, IEEE Transactions on Information Theory, vol. 21, pp. 32-40, January 1975.

[17] D. Comaniciu, V. Ramesh, and P. Meer, “Kernel-based object tracking”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 564-577, May 2003.

[18] D. Freedman and P. Kisilev, “Fast mean shift by compact density representation”, IEEE Conference on Computer Vision and Pattern Recognition, pp. 1818-1825, June 2009.

[19] F. L. Wang, S. Y. Yu, and J. Yang, “Robust and efficient fragments-based tracking using mean shift”, AEU - International Journal of Electronics and Communications, vol. 64, pp. 614-623, July 2010.

[20] F. Porikli and O. Tuzel, “Multi-kernel object tracking”, IEEE International Conference on Multimedia and Expo, pp. 1234–1237, July 2005.

[21] C. Yang, R. Duraiswami, and L. Davis, “Efficient mean-shift tracking via a new similarity measure”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 176–183, June 2005.

[22] R. V. Babu, P. Pe´rez, and P. Bouthemy, “Robust tracking with motion estimation and local Kernel-based color modeling”, Image and Vision Computing, vol. 25, pp.1205–1216, August. 2007.

[23] S. Feng, Q. Guan, S. Xu and F. Tan, “Human tracking based on mean shift and Kalman Filter”, International Conference on Artificial Intelligence and Computational Intelligence,2009.

[24] P. Pe´rez, C. Hue, J. Vermaak, M. Gangnet, “Color-based probabilistic tracking”, Proceedings of European Conference on Computer Vision, pp. 661-675, 2002.

[25] K. Nummiaro, E. Koller-Meier, and L. V. Gool, “An adaptive color based particle filter”, Image and Vision Computing, vol. 21, pp. 99–110, 2003.

[26] D. Murray and A. Basu, “Motion tracking with an active camera”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, May 1994.

[27] C. W. Lin, C. M. Wang, Y. J. Chang, and Y. C. Chen, “Real-time object extraction and tracking with an active camera using image mosaics”, Proceedings of the IEEE Workshop on Multimedia Signal Processing, pp.

46

149-152, December 2002.

[28] R. T. Collins, O. Amidi, and T. Kanade, “An active camera system for acquiring multi-view video”, Proceedings of the International Conference on Image Processing, September 2002.

[29] L. Fiore, D. Fehr, R. Bodor, A. Drenner, G. Somasundaram and N.

Papanikolopoulos, “Multi-camera human activity monitoring”, Journal of Intelligent Robotic Systems, vol. 52, pp.5-43, May 2008.

[30] A. R. Smith, “Color Gamut Transform Pairs”, SIGGRAPH 78 Conference Proceedings, vol. 12, pp. 12-19, August 1978.

[31] http://en.wikipedia.org/wiki/HSV_color_space#Conversion_from_RGB_to_HSL _or_HSV

[32] http://www.mathworks.com/access/helpdesk/help/toolbox/images/f8-20792.html [33] Y. Cheng, “Mean shift, mode seeking, and Clustering”, IEEE Transactions on

Pattern Analysis and Machine Intelligence, vol. 17, pp. 790-799, Aug. 1995.

[34] http://www.commfront.com/RS232_Examples/CCTV/Pelco_D_Pelco_P_Examp les_Tutorial2.HTM#1

[35] http://en.wikipedia.org/wiki/PID_controller