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International Journal of Reconfigurable Computing
Volume 2008, Article ID 636145, 8 pages
Research Article

FPGA-Based Embedded Motion Estimation Sensor

Electrical and Computer Engineering Department, Brigham Young University, Provo, UT 84602, USA

Received 27 March 2008; Accepted 24 June 2008

Academic Editor: Fernando Pardo

Copyright © 2008 Zhaoyi Wei et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Accurate real-time motion estimation is very critical to many computer vision tasks. However, because of its computational power and processing speed requirements, it is rarely used for real-time applications, especially for micro unmanned vehicles. In our previous work, a FPGA system was built to process optical flow vectors of 64 frames of image per second. Compared to software-based algorithms, this system achieved much higher frame rate but marginal accuracy. In this paper, a more accurate optical flow algorithm is proposed. Temporal smoothing is incorporated in the hardware structure which significantly improves the algorithm accuracy. To accommodate temporal smoothing, the hardware structure is composed of two parts: the derivative (DER) module produces intermediate results and the optical flow computation (OFC) module calculates the final optical flow vectors. Software running on a built-in processor on the FPGA chip is used in the design to direct the data flow and manage hardware components. This new design has been implemented on a compact, low power, high performance hardware platform for micro UV applications. It is able to process 15 frames of image per second and with much improved accuracy. Higher frame rate can be achieved with further optimization and additional memory space.