Multi-Label Human Activity Recognition on Image Using Deep Learning
Pavel Nikolaev · 2019
This paper describes the model of convolutional neural network which is designed for multi-label human activity recognition.The possibilities of using activity recognition systems in the daily life of a person are considered.As part of this work, the study is conducted for the method of recognizing human activity on an image that can be obtained from a surveillance camera.To obtain more accurate recognition results, the network model used technology of transfer learning.Several pre-trained convolutional networks are considered using two types of transfer learning in order to find the best solution.The deep learning networks for solving the problem are implemented in Python using deep learning libraries.Considered models are trained to recognize binary multi-label human activity.Training and testing are performed on images collected by the author.The article also provides the obtained training and testing results of different models of convolutional neural networks.The data obtained are tabulated and also presented in graphical form.