JSSC 2024第6期Digital Circuits65nm

HGRP A 181- µW Real-Time Hand Gesture Recognition Processor Based on Bi-Directio

提出一种基于双向卷积的181µW超低功耗实时手势识别处理器。

65nm CMOS, 0.58V, 181µW

手势识别超低功耗双向卷积特征提取实时处理

▸双向卷积特征提取提高旋转抗性

▸自适应激活手势识别核心降低动态功耗

▸全流水线特征提取引擎减少处理延迟

Abstract

Hand gesture recognition (HGR) has become a prevalent human–computer interaction (HCI) approach on smart edge devices. The existing HGR systems suffer from either extensive power consumption and latency or low recognition rates under complex backgrounds. This article proposes an ultralow power real-time HGR system for the Internet-of- Things (IoT) applications through algorithm and hardware co-optimization. On the algorithm aspect, this work utilizes color- and depth-based hand segmentation for