A VGA 30fps affine motion model estimation VLSI for real-time video segmentation

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Abstract

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 an image division method and a binary weight method to the original algorithm reduces data traffic and hardware costs. A pixel sampling method is proposed that reduces the clock frequency by 50%. The pixel pipeline architecture and a frame overlap method double throughput. The processor was prototyped on an FPGA; its function and performance were subsequently verified. It was also implemented as an ASIC. The core size is 5.0 × 5.0 mm2 in 0.18 μm process, standard cell technology. The ASIC can accommodate a VGA 30 fps video with 120 MHz clock frequency. Copyright© 2010.

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Yunbe, Y., Miyama, M., & Matsuda, Y. (2010). A VGA 30fps affine motion model estimation VLSI for real-time video segmentation. In IEICE Transactions on Information and Systems (Vol. E93-D, pp. 3284–3293). Institute of Electronics, Information and Communication, Engineers, IEICE. https://doi.org/10.1587/transinf.E93.D.3284

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