Abstract
The problem of object tracking is of considerable interest in the scientific community and it is still an open and active field of research. In this paper we address the comparison of two different specific purpose architectures for object tracking based on motion and colour segmentation. On one hand, we have developed a new multi-object segmentation device based on an existing optical flow estimation system. This architecture allows video tracking of fast moving objects based on high speed acquisition cameras. On the other hand, the second approach consists on real time filtering of chromatic components. Multi-object tracking is performed based on segmentation of pixel neighbourhoods according to a predefined colour. In this contribution we evaluate the two methods, comparing their performance, resource consumption and finally, we discuss which architecture fits better in different working cenarios.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Manohar, V., et al.: Performance Evaluation of Object Detection and Tracking in Video. In: Narayanan, P.J., Nayar, S.K., Shum, H.-Y. (eds.) ACCV 2006. LNCS, vol. 3852, pp. 151–161. Springer, Heidelberg (2006)
Hsiao, Y.T., et al.: Robust multiple objects tracking using image segmentation and trajectory estimation scheme in video frames. Image and Vision Computing 24, 1123–1136 (2006)
Ellis, T.J.: Performance metrics and methods for tracking in surveillance. In: 3rd IEEE Workshop on PETS, Copenhagen, Denmark, pp. 26–31. IEEE Computer Society Press, Los Alamitos (2002)
Pérez, P., et al.: Color-based probabilistic tracking. In: Heyden, A., et al. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 661–675. Springer, Heidelberg (2002)
Hamamoto, T., Nagao, S., Aizawa, K.: Real-time objects tracking by using smart image sensor and FPGA. In: IEEE Image Processing Proc. Intern. Conf., vol. 3, pp. 441–444. IEEE Computer Society Press, Los Alamitos (2002)
Shi, J., Tomasi, C.: Good Features to Track. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600. IEEE Computer Society Press, Los Alamitos (1994)
Yilmaz, A., Li, X., Shah, M.: Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 26(11), 1531–1536 (2004)
Zivkovic, Z., Kröse, B.: An EM-like Algorithm for Color-Histogram-based Tracking. In: IEEE Conf. on Comp. Vision and Pattern Recognition, vol. 1, June 2004, pp. 798–803. IEEE Computer Society Press, Los Alamitos (2004)
Díaz, J., et al.: FPGA based real-time optical-flow system. IEEE Trans. on Circ. and Syst. for Video Tec. 16(2), 274–279 (2006)
Barron, J.L., Fleet, D.J., Beauchemin, S.: Performance of optical-flow techniques. International Journal of Computer Vision 12(1), 43–77 (1994)
Lucas, B.D., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proc. of the DARPA Image Understanding Workshop, pp. 121–130 (1984)
McCane, B., et al.: On Benchmarking Optical Flow. Computer Vision and Image Understanding 84, 126–143 (2001)
Liu, H.C., et al.: Accuracy vs. Efficiency Trade-offs in Optical Flow Algorithms. Comp. Vis. and Image Understanding 72(3), 271–286 (1998)
Díaz, J., et al.: Real time optical flow processing system. In: Becker, J., Platzner, M., Vernalde, S. (eds.) FPL 2004. LNCS, vol. 3203, pp. 617–626. Springer, Heidelberg (2004)
Díaz, J., et al.: Highly parallelized architecture for image motion estimation. In: Bertels, K., Cardoso, J.M.P., Vassiliadis, S. (eds.) ARC 2006. LNCS, vol. 3985, pp. 75–86. Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Tomasi, M., Díaz, J., Ros, E. (2007). Real Time Architectures for Moving-Objects Tracking. In: Diniz, P.C., Marques, E., Bertels, K., Fernandes, M.M., Cardoso, J.M.P. (eds) Reconfigurable Computing: Architectures, Tools and Applications. ARC 2007. Lecture Notes in Computer Science, vol 4419. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71431-6_35
Download citation
DOI: https://doi.org/10.1007/978-3-540-71431-6_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71430-9
Online ISBN: 978-3-540-71431-6
eBook Packages: Computer ScienceComputer Science (R0)