Vision Based Human Activity Recognition: A Comprehensive Review of Methods & Techniques

Abstract

Human Activity Recognition (HAR) plays an important role in various domains. There are four major phases of HAR: Data Collection, Pre-Processing, Feature Extraction and Training. Out of these, Pre-processing and Feature Extraction requires massive attention, as these are the building block for the training phase. In this paper, an extensive and thorough review of the state-of-the-art methods is given along with identification of challenging areas of HAR ecosystem. Primarily, trends in research outflowing in the area of Vision based approach is effectively studied in the present review. Further, a consideration with state-of-the-art applications and the importance of handcrafted and learning based features is emphasized. The review presented in this paper, gives the details of available training datasets of HAR and also discusses the popular publicly available datasets. The readers will be benefitted with a comprehensive review of the extensive work done in the field of HAR and its Vision based approaches.