A VGA 30 FPS Affine Motion Estimation Processor for Real-Time Video Segmentation

Y. Yunbe, M. Miyama, and Y. Matsuda (Japan)


Affine motion model, real-time, video segmentation, VLSI, and FPGA


This paper describes an affine motion estimation processor for real-time video segmentation. The processor estimates the dominant motion of a target region with affine parameters. The processor is based on the Pseudo M-estimator algorithm. Introduction of a binary weight method and an image division method to the original algorithm reduces data traffic and hardware costs. In addition, a pixel sampling method can reduce the clock frequency by 50%. The pixel pipeline architecture and a frame overlap method double throughput. The proposed VLSI architecture can accommodate a VGA 30-fps video with 120 MHz clock frequency. The processor was implemented prototypically on an FPGA; its function and performance were subsequently verified. The estimated core size is 13.15 mm2 with 0.18-┬Ám process, standard cell technology.

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