AN EXTENDED MOTION-ESTIMATION ARCHITECTURE APPLIED TO SHAPE RECOGNITION (FriAmPO1)

Author(s) : Jason Schlessman (Princeton University, United States of America) Sankalita Saha (University of Maryland, United States of America) Wayne Wolf (Princeton University, United States of America) Shuvra Bhattacharya (University of Maryland, United States of America)

Abstract : An architecture for shape recognition is presented, with emphasis on low-latency and power efficiency. This architecture is an extension of an existing architecture used for motion estimation. A number of algorithms were mapped to this architecture. Bounds related to power are given per frame for memory access rates. Face detection within CIPR CIF sequences was used as a target application, with feasible frame rates of 30fps attained. Power results for this extended architecture correlate with power consumption of the existing architecture.

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