REAL-TIME HORN-SCHUNCK OPTICAL FLOW HARDWARE ARCHITECTURE FOR HIGH ACCURACY MOTION ESTIMATION
The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm used to compute motion estimation from the apparent motion of image sequences. To achieve real-time performance and high accuracy estimation for real-time system especially for machine vision application, numerous effo...
| Main Author: | RUZALI, RUZALI |
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| Format: | Thesis |
| Language: | English |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-utpedia.23030 / |
| Published: |
2012
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| Subjects: | |
| Online Access: |
http://utpedia.utp.edu.my/23030/1/Ruzali%27s%20Thesis%20v.4%2020120719%20after%20viva-voce%20%28final%29.pdf http://utpedia.utp.edu.my/23030/ |
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| Summary: |
The optical flow constraint equation of Horn-Schunck (OFCE-HS) is an algorithm
used to compute motion estimation from the apparent motion of image sequences. To
achieve real-time performance and high accuracy estimation for real-time system
especially for machine vision application, numerous efforts have been put to
implement the OFCE-HS algorithm into hardware. However, so far there has not been
a single solution reported to have achieved both real-time performance and high
estimation accuracy. Therefore, the work reported in this thesis was set out with an
objective to come up with a hardware solution to address the real-time and accuracy
problem aforementioned. The objective was achieved by implementing high
throughput hardware architecture that is able to support the high iteration (i.e. a
minimum of fifty iterations) required by the OFCE-HS algorithm to achieve
acceptable accuracy. In addition to the pipeline processing, two partitioning
techniques were successfully implemented; first, on the frame of the image sequences
and second, on the loop of the iterations. The optimized OFCE-HS hardware
architecture was implemented on the FPGA Xilinx Spartan-3A DSP 1800A. |
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