FPGA-based real-time object tracking for mobile robot

This paper proposes an embedded vision system for real-time moving object tracking using modified mean-shift algorithm for mobile robot application. This design of modified mean-shift algorithm fully utilizing the advanced parallelism of Field Programmable Gate Arrays (FPGA) is capable of processing real-time PAL video of 720∗576 at 25 fps. This hardware implementation realizes time-consumed color space transformation using pipeline operations, which completely removes the dependence of off-chip RAM memory. In addition, this system incorporates adaptive kernel based mass center calculation method to balance the tracking complication and precision. Finally, the time division multiplex (TDM) technology obviously saves the FPGA hardware resources. As a result, the feasibility and tracking robustness of this implementation have been demonstrated through realtime tracking videos.

[1]  Huosheng Hu,et al.  FPGA-based colour image classification for mobile robot navigation , 2005, 2005 IEEE International Conference on Industrial Technology.

[2]  Huang Xian-wu Non-Rigid Object Tracking by Anisotropic Kernel Mean Shift , 2007 .

[3]  Dorin Comaniciu,et al.  Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[4]  Dimitrios K. Iakovidis,et al.  An FPGA-based architecture for real time image feature extraction , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[5]  Dah-Jye Lee,et al.  FPGA-based Real-time Optical Flow Algorithm Design and Implementation , 2007, J. Multim..

[6]  Yizong Cheng,et al.  Mean Shift, Mode Seeking, and Clustering , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Donald G. Bailey,et al.  FPGA based Remote Object Tracking for Real-time Control , 2005 .

[8]  Jason Schlessman,et al.  Hardware/Software Co-Design of an FPGA-based Embedded Tracking System , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[9]  Usman Ali,et al.  FPGA/soft-processor based real-time object tracking system , 2009, 2009 5th Southern Conference on Programmable Logic (SPL).

[10]  齐苏敏,et al.  Non-Rigid Object Tracking by Anisotropic Kernel Mean Shift , 2007 .

[11]  Khaled Benkrid,et al.  Design and implementation of a 2D convolution core for video applications on FPGAs , 2002, Third International Workshop on Digital and Computational Video, 2002. DCV 2002. Proceedings..