Affiliation:
1. Auckland University of Technology, New Zealand
Abstract
Human action recognition is a fundamental research problem in computer vision. The accuracy of human action recognition has important applications. In this book chapter, the authors use a YOLOv7-based model for human action recognition. To evaluate the performance of the model, the action recognition results of YOLOv7 were compared with those using CNN+LSTM, YOLOv5, and YOLOv4. Furthermore, a small human action dataset suitable for YOLO model training is designed. This data set is composed of images extracted from KTH, Weizmann, MSR data sets. In this book chapter, the authors make use of this data set to verify the experimental results. The final experimental results show that using the YOLOv7 model for human action recognition is very convenient and effective, compared with the previous YOLO model.