基于深度学习的人类行为识别研究综述

Fang-Fang Hao, Jie Liu, Xiangzhen Chen
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引用次数: 2

摘要

人类行为识别是计算机视觉领域的一个研究热点。本文介绍和分析了近年来视频领域中人体运动和行为识别的方法,介绍了构建网络的主要方法和优化网络参数以提高模型识别效果的方法,以及常用的数据集。目前,人类行为识别仍有待进一步研究,在准确率、模型参数数量、计算量等方面仍存在较大挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Human Behavior Recognition Based on Deep Learning
Human behavior recognition is a research hotspot in the field of computer vision. This paper introduces and analyzes the methods of human motion and behavior recognition in the field of video in recent years, describes the main ways to build the network and the methods to optimize the network parameters to improve the model recognition effect, as well as the commonly used data sets. At present, human behavior recognition still needs to be further studied, and there are still great challenges in accuracy, number of model parameters and calculation amount.
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