A review on learning-based algorithms for human activity recognition Online publication date: Thu, 15-Feb-2024
by Richa Mishra
International Journal of Data Analysis Techniques and Strategies (IJDATS), Vol. 15, No. 4, 2023
Abstract: Human activity recognition (HAR) is an essential system that helps to identify, track and recognise human activities with the help of learning-based approaches in diverse areas of HCI, surveillance, health monitoring system, etc. The performance of the system is limited due to several factors such as placement of sensors, overfitting and underfitting of machine learning models, privacy issues, tracking GPS-based activities, cluttered background, etc. However, several comprehensive review papers have been published focusing on the state-of-the-art approaches using learning-based algorithms either in sensor-based HAR, vision-based HAR or both. This paper focuses on the research work to improve performance of the system using learning-based techniques focusing on video-based, sensor-based and Wi-Fi-based HAR. In addition, we have discussed the current state-of-the-art approaches, their merits and limitations, focused on the public datasets used for the performance evaluation, challenges and future directions for HAR.
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