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Hamamatsu, Japan

Yazawa Y.,SANEI HYTECHS Co. | Yoshimi T.,SANEI HYTECHS Co. | Tsuzuki T.,SANEI HYTECHS Co. | Dohi T.,SANEI HYTECHS Co. | And 3 more authors.
IEICE Transactions on Information and Systems | Year: 2015

Much effort has been applied to research on object detection by statistical learning methods in recent years, and the results of that work are expected to find use in fields such as ITS and security. Up to now, the research has included optimization of computational algorithms for real-time processing on hardware such as GPU's and FPGAs. Such optimization most often works only with particular parameters, which often forfeits the flexibility that comes with dynamic changing of the target object. We propose a hardware architecture for faster detection and flexible target reconfiguration while maintaining detection accuracy. Tests confirm operation in a practical time when implemented in an FPGA board. Copyright © 2015 The Institute of Electronics, Information and Communication Engineers. Source

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