Abstract
Human activity recognition (HAR) systems attempt to automatically identify and analyze human activities using acquired information from various types of sensors. Although several extensive review papers have already been published in the general HAR topics, the growing technologies in the field as well as the multi-disciplinary nature of HAR prompt the need for constant updates in the field. In this respect, this paper attempts to review and summarize the progress of HAR systems from the computer vision perspective. Indeed, most computer vision applications such as human computer interaction, virtual reality, security, video surveillance and home monitoring are highly correlated to HAR tasks. This establishes new trend and milestone in the development cycle of HAR systems. Therefore, the current survey aims to provide the reader with an up to date analysis of vision-based HAR related literature and recent progress in the field. At the same time, it will highlight the main challenges and future directions.
Highlights
Human activity recognition is often associated to the process of determining and naming activities using sensory observations [213]
We explore in this paper, the state-of-the-art of Human activity recognition (HAR) methods from different point of views, and categorize the general HAR task according to several criteria which are discussed
The need to understand and interpret effectively human activities has become unavoidable in several applications of computer vision, human computer interaction (HCI), robotics, security and home monitoring
Summary
Human activity recognition is often associated to the process of determining and naming activities using sensory observations [213]. A human activity (HA) refers to the movement (s) of one or several parts of the person’s body This can be either atomic or composed of many primitive actions performed in some sequential order. The work of [223] aims at ensuring a good implementation of various Human Computer interaction systems. To this end, the underlined HAR systems are generally preceded by an activity detection task. The underlined HAR systems are generally preceded by an activity detection task This consists of the temporal identification and localization of such activity in the scene in a way to boost the understanding of the ongoing event. The activity recognition task can be divided into two classes: classification and detection
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