Document Type thesis Author Name Zhu, Sichao Email Address zhusichao88 at gmail.com URN etd-043014-170044 Title Real time implementation of SURF algorithm on FPGA platform Degree MS Department Electrical & Computer Engineering Advisors Xinming Huang, Advisor Lifeng Lai, Committee Member Taskin Padir, Committee Member Keywords real time. video SURF FPGA Implementation Date of Presentation/Defense 2014-04-28 Availability restricted
Too many traffic accidents are caused by driversí failure of noticing buildings, traffic sign and other objects. Video based scene or object detection which can easily enhance driversí judgment performance by automatically detecting scene and signs. Two of the recent popular video detection algorithms are Background Differentiation and Feature based object detection. The background Differentiation is an efficient and fast way of observing a moving object in a relatively stationary background, which makes it easy to be implemented on a mobile platform and performs a swift processing speed. The Feature based scene detection such like the Speeded Up Robust Feature (SURF), is an appropriate way of detecting specific scene with accuracy and rotation and illumination invariance. By comparison, SURF computational expense is much higher, which remains the algorithm limited in real time mobile platform. In this thesis, I present two real time tracking algorithms, Differentiation based and SURF based scene detection systems on FPGA platform. The proposed hardware designs are able to process video of 800*600 resolution at 60 frames per second, the video clock rate is 40 MHz.
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