2024年10月4日 · 主流的传统方法有轮廓剪影（human silhouette）、 时空兴趣点（space-time interest points）、人体关节点 （human joint point）和运动轨迹（trajectories）。依照 网络结构将基于深度学习行为识别划分为三大类： 双流网络（two-stream network）、3D 卷积神经网络（3D

2022年1月1日 · In order to solve the disadvantages of traditional human behavior recognition methods such as poor robustness, inconvenience of wearing and privacy violation, this paper proposes a human behavior recognition model based on the improved EfficientNet.

2021年12月10日 · This paper presents the design and mathematical modeling of a human behavior recognition system image processing and pattern recognition. Human behavior recognition is a framework for understanding human behavior.

In this paper, we investigated a human behaviour recognition using deep learning based on YOLOv3 model. After a number of experiments conducted, our YOLOv3 model had shown to achieve 80.20% of accuracy in human behaviour recognition with the speed of approximate 15 fps using GPU acceleration.

传统行为识别模型主要包括基于轮廓剪影、时空兴趣点、人体关节点、运动轨迹的特征描述方法。 其中改进的密集轨迹方式拥有良好的鲁棒性和可靠性;深度学习网络架构主要有双流网络、3D卷积网络和混合网络。 首先,重点阐述了各行为识别算法的主要研究思路与创新点,并介绍了每类算法的模型架构、算法特色、适用情境等。 然后,对广泛使用的公共行为数据库进行了分类阐述,着重对HMDB51和UCF101数据集进行了详细介绍,比较分析了传统方法和深度学习算法在各数据集上 …

2019年10月23日 · Among various implementation, behavior recognition based on WiFi CSI (channel state information) has drawn wide attention due to its major advantages. This paper investigates more than 100 latest CSI based behavior recognition applications within the last 6 years and presents a comprehensive survey from every aspect of human behavior recognition.

2022年6月21日 · This paper systemizes and introduces behavior recognition algorithms based on deep learning proposed in recent years, then focuses on a series of behavior recognition algorithms based on image and bone data; deeply analyzes their theories and performance, and finally, puts forward further prospects.

2024年2月1日 · Human Activity Recognition technology typically involves the identification and classification of human behaviors and actions using video images and sensor data. Wearable sensor devices, such as smart bracelets and watches, possess advantages such as low cost, easy wear ability, and minimal computational overhead.

2021年11月23日 · Human activity recognition (HAR) is to recognize the actions performed by a person through a series of observations of the person and their surroundings. To improve user experience, HAR has been widely used in medical care, social security, behavior analysis, traffic safety and other industries.

2021年10月23日 · In this study, we survey systematically the popular methods, algorithms, models and well-known action datasets in human behavior analysis in the past two decades. In addition, the advantages and disadvantages of the methods are discussed and propitious future research directions are also presented.