[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5573/JSTS.2017.17.3.473

A Memory-efficient Hand Segmentation Architecture for Hand Gesture Recognition in Low-power Mobile Devices

Choi, Sungpill (Department of Electrical Engineering KASIT)
Park, Seongwook (Department of Electrical Engineering KASIT)
Yoo, Hoi-Jun (Department of Electrical Engineering KASIT)

Publication Information

JSTS:Journal of Semiconductor Technology and Science / v.17, no.3, 2017 , pp. 473-482 More about this Journal

Abstract

Hand gesture recognition is regarded as new Human Computer Interaction (HCI) technologies for the next generation of mobile devices. Previous hand gesture implementation requires a large memory and computation power for hand segmentation, which fails to give real-time interaction with mobile devices to users. Therefore, in this paper, we presents a low latency and memory-efficient hand segmentation architecture for natural hand gesture recognition. To obtain both high memory-efficiency and low latency, we propose a streaming hand contour tracing unit and a fast contour filling unit. As a result, it achieves 7.14 ms latency with only 34.8 KB on-chip memory, which are 1.65 times less latency and 1.68 times less on-chip memory, respectively, compare to the best-in-class.

Keywords

Hand gesture; low latency; memory-efficient design; image processing; human computer interaction;

Citations & Related Records

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