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.