NDLI: An 86 mW 98GOPS ANN-Searching Processor for Full-HD 30 fps Video Object Recognition With Zeroless Locality-Sensitive Hashing

Content Provider	IEEE Xplore Digital Library
Author	Gyeonghoon Kim Jinwook Oh Seungjin Lee Hoi-Jun Yoo
Copyright Year	1966
Abstract	Approximate nearest neighbor (ANN) searching is an essential task in object recognition. The ANN-searching stage, however, is the main bottleneck in the object recognition process due to increasing database size and massive dimensions of keypoint descriptors. In this paper, a high throughput ANN-searching processor is proposed for high-resolution (full-HD) and real-time (30 fps) video object recognition. The proposed ANN-searching processor adopts an interframe cache architecture as a hardware-oriented approach and a zeroless locality-sensitive-hashing (zeroless-LSH) algorithm as a software-oriented approach to reduce the external memory bandwidth required in nearest neighbor searching. A four-way set associative on-chip cache has a dedicated architecture to exploit data correlation at the frame-level. Zeroless-LSH minimizes data transactions from external memory at the vector-level. The proposed ANN-searching processor is fabricated as part of an object recognition SoC using a 0.13 μm 6 metal CMOS technology. It achieves 62 720 vectors/s throughput and 1140 GOPS/W power efficiency, which are 1.45 and 1.37 times higher than the state-of-the-art, respectively, enabling real-time object recognition for full-HD 30 fps video streams.
Sponsorship	IEEE Solid-State Circuits Society IEEE Electron Devices Society IEEE Circuits and Systems Society Japan Society of Applied Physics (JSAP) IEEE Microwave Theory and Techniques Society IEEE San Francisco Section Bay Area Council Univ. PA IEEE
Starting Page	1615
Ending Page	1624
Page Count	10
File Size	2913202
File Format	PDF
ISSN	00189200
Volume Number	48
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Indexes Object recognition System-on-chip Search problems Throughput zeroless-LSH Approximate nearest neighbor (ANN) searching processor ANN searching interframe cache architecture locality-sensitive-hashing (LSH)
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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