Real-time Optical-flow Computation for Motion Estimation under Varying Illumination Conditions
The optical flow approach has emerged as a major technique for estimating object motion in image sequences. However, the obtained results by most optical flow techniques are poor because they are strongly affected by large illumination changes and by motion discontinuities. On the other hand, there have been two thrusts in the development of optical flow algorithms. One has emphasized higher accuracy; the other faster implementation. These two thrusts have been independently pursed, without addressing the accuracy vs. efficiency trade-offs. The optical flow computation requires high computing resources and is highly affected by changes in the illumination conditions in most of the existing techniques. In this paper, a new strategy for image sequence processing is proposed. The data reduction achieved with this strategy allows a faster optical flow computation. In addition, the proposed architecture is a hardware custom implementation in EP1S60F1020 FPGA showing the achieved performance.
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