(A) real-time optical flow estimation processor for action recognition in mobile devices = 모바일 기기에서의 행동인식을 위한 실시간 광류 추정 프로세서

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A 99.4 fps optical flow estimation (OFE) processor with image tiling is proposed for action recognition in mobile devices. The OFE is essential for the high action recognition accuracy. However, it is unsuitable for real-time constraint in a mobile computing environment because it requires a huge amount of external memory accesses (EMAs) and matrix computations. For mitigating the external memory bandwidth requirement, this paper proposes the tile-based hierarchical OFE. It divides input images into several tiles and enables intermediate data reusing with 326.4 KB on-chip memory and 175.8 MB/s external memory bandwidth. Moreover, a background decision unit with early termination is proposed to reduce computation workload. It gets rid of unnecessary matrix computation by terminates the computation early for zero optical flow region. As a result, the proposed features reduce external memory bandwidth by 99.3 % and increase throughput by 50.7 %, respectively. The proposed $12.8 mm^2$ OFE processor is implemented in 65 nm CMOS technology, and it achieves the real-time OFE with 99.4 frames-per-second (fps) throughput for an image resolution of QVGA (320 × 240).
Advisors
Yoo, Hoi-Junresearcher유회준researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.2,[iii, 21 p. :]

Keywords

Optical flow estimation▼aaction recognition▼atile-based processing▼aearly termination▼ahigh throughput ASIC; 광류 추정▼a행동 인식▼a타일 기반 처리▼a조기 종료▼a고처리량 ASIC

URI
http://hdl.handle.net/10203/266859
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=843416&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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