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Visual Vocabulary Processor Based on Binary Tree Architecture for Real-Time Object Recognition in Full-HD Resolution

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6 Author(s)
Tse-Wei Chen ; VLSI Design & Educ. Center (VDEC), Univ. of Tokyo, Tokyo, Japan ; Yu-Chi Su ; Keng-Yen Huang ; Yi-Min Tsai
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Feature matching is an indispensable process for object recognition, which is an important issue for wearable devices with video analysis functionalities. To implement a low-power SoC for object recognition, the proposed visual vocabulary processor (VVP) is employed to accelerate the speed of feature matching. The VVP can transform hundreds of 128-D SIFT vectors into a 64-D histogram for object matching by using the binary-tree-based architecture, and 16 calculators for the computations of the Euclidean distances are designed for each of the two processors in each level. A total of 126 visual words can be saved in the six-level hierarchical memory, which instantly offers the data required for the matching process, and more than 5 times of bandwidth can be saved compared with the non-binary-tree-based architecture. As a part of the recognition SoC, the VVP is implemented with the 65-nm CMOS technology, and the experimental results show that the gate count and the average power consumption are 280 K and 5.6 mW, respectively.

Published in:

Very Large Scale Integration (VLSI) Systems, IEEE Transactions on  (Volume:20 ,  Issue: 12 )

Date of Publication:

Dec. 2012

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