Activity recognition systems are a large field of research and development, currently with a focus on advanced machine learning algorithms, innovations in the field of hardware architecture, and on decreasing the costs of monitoring while increasing safety. Human action recognition (HAR) research is hot in computer vision, but high precision recognition of human action in the complex background is still an open question. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs, which are driven by tasks and uncertain. In this paper, type of deep model convolutional neural network (CNN) is proposed for HAR that can act directly on the raw inputs.
Neha Nilesh Jadhav Sarnaik (2020); Human Activity Recognition using CNN; International Journal of Scientific and Research Publications (IJSRP)
10(02) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.10.02.2020.p9804