Abstract

The field of human event recognition using visual data in smart environments has emerged as a fruitful and successful area of study, with extensive research and development efforts driving significant advancements. These advancements have not only provided valuable insights, but also led to practical applications in various domains. In this context, human actions, activities, interactions, and behaviors can all be considered as events of interest in smart environments. However, when it comes to smart classrooms, there is a lack of unified consensus on the definition of the term “human event.” This lack of agreement presents a significant challenge for educators, researchers, and developers, as it hampers their ability to precisely identify and classify the specific situations that are relevant within the educational context. The aim of this paper is to address this challenge by conducting a systematic literature review of relevant events in smart classrooms, with a focus on their applications in assistive technology. The review encompasses a comprehensive analysis of 227 published documents spanning from 2012 to 2022. It delves into key algorithms, methodologies, and applications of vision-based event recognition in smart environments. As the primary outcome, the review identifies the most significant events, classifying them according to single person behavior, or multiple-person interactions, or object-person interactions. It also examines their practical applications within the educational context. The paper concludes with a discussion on the relevance and practicality of vision-based human event recognition in smart classrooms, particularly in the post-COVID era.

中文翻译：

---

使用计算机视觉的智能教室中的人体事件识别：系统文献综述

摘要

在智能环境中使用视觉数据进行人类事件识别领域已成为一个富有成效且成功的研究领域，广泛的研究和开发工作推动了重大进步。这些进步不仅提供了宝贵的见解，而且还导致了各个领域的实际应用。在这种情况下，人类的行为、活动、交互和行为都可以被视为智能环境中的感兴趣事件。然而，对于智慧教室，对于“人的事件”一词的定义却缺乏统一的共识。这种缺乏共识给教育工作者、研究人员和开发人员带来了重大挑战，因为这妨碍了他们精确识别和分类教育环境中相关的特定情况的能力。本文的目的是通过对智能教室中的相关事件进行系统的文献综述来应对这一挑战，重点关注其在辅助技术中的应用。该综述对 2012 年至 2022 年期间发布的 227 篇文档进行了全面分析。它深入研究了智能环境中基于视觉的事件识别的关键算法、方法和应用。作为主要结果，审查确定了最重要的事件，并根据单人行为、多人交互或物人交互对它们进行分类。它还检查了它们在教育背景下的实际应用。本文最后讨论了基于视觉的人类事件识别在智能教室中的相关性和实用性，特别是在后新冠时代。