本书系统、全面、及时地回顾了V-HAR，涵盖了V-HAR的相关任务、前沿技术和应用，尤其是基于深度学习的方法。由于各种传感器的可用性、实时数据流以及计算机视觉、机器学习等方面的进步，人类活动识别（HAR）领域已成为最热门的研究课题之一。HAR可广泛应用于许多场景，例如医疗诊断、视频监控、公共治理，也可用于人机交互应用。在哈尔，人们可以识别各种人类活动，如走路、跑步、坐、睡觉、站立、洗澡、做饭、开车、异常活动等。可以从可穿戴传感器或加速计或通过视频帧或图像收集数据；在所有传感器中，基于视觉的传感器以其低成本、高质量和非侵入性的特点成为目前应用最广泛的传感器。因此，基于视觉的人类活动识别（V-HAR）是所有HAR技术中最重要、最常用的一类。
Vision-Based Human Activity Recognition
This book offers a systematic, comprehensive, and timely review on V-HAR, and it covers the related tasks, cutting-edge technologies, and applications of V-HAR, especially the deep learning-based approaches. The field of Human Activity Recognition (HAR) has become one of the trendiest research topics due to the availability of various sensors, live streaming of data and the advancement in computer vision, machine learning, etc. HAR can be extensively used in many scenarios, for example, medical diagnosis, video surveillance, public governance, also in human–machine interaction applications. In HAR, various human activities such as walking, running, sitting, sleeping, standing, showering, cooking, driving, abnormal activities, etc., are recognized. The data can be collected from wearable sensors or accelerometer or through video frames or images; among all the sensors, vision-based sensors are now the most widely used sensors due to their low-cost, high-quality, and unintrusive characteristics. Therefore, vision-based human activity recognition (V-HAR) is the most important and commonly used category among all HAR technologies.
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