This paper is published in Volume-6, Issue-3, 2020
Area
Electronics and Communication Engineering
Author
M. Sohan Raj Kumar
Co-authors
Dr. Syed Abudhagir Umar, M. Phillips Robert, J. Nagendra Vara Prasad, CH. Prasad, Talluri Sairam
Org/Univ
B. V. Raju Institute of Technology, Hyderabad, Telangana, India
Pub. Date
06 May, 2020
Paper ID
V6I3-1166
Publisher
Keywords
CNN, HAR, Prediction, Neural Networks

Citationsacebook

IEEE
M. Sohan Raj Kumar, Dr. Syed Abudhagir Umar, M. Phillips Robert, J. Nagendra Vara Prasad, CH. Prasad, Talluri Sairam. Vision-based human activity recognition using CNN, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
M. Sohan Raj Kumar, Dr. Syed Abudhagir Umar, M. Phillips Robert, J. Nagendra Vara Prasad, CH. Prasad, Talluri Sairam (2020). Vision-based human activity recognition using CNN. International Journal of Advance Research, Ideas and Innovations in Technology, 6(3) www.IJARIIT.com.

MLA
M. Sohan Raj Kumar, Dr. Syed Abudhagir Umar, M. Phillips Robert, J. Nagendra Vara Prasad, CH. Prasad, Talluri Sairam. "Vision-based human activity recognition using CNN." International Journal of Advance Research, Ideas and Innovations in Technology 6.3 (2020). www.IJARIIT.com.

Abstract

Human Activity Recognition (HAR) is a commonly discussed topic in computer vision. HAR implementations include representations such as health care and contact between the human and computer systems. When the imaging technology progresses and the camera system improves, there is a relentless proliferation of innovative approaches for HAR. Human activity recognition is an important component of many creative and human-behavior driven programs. The ability to recognize various human activities enables the development of an intelligent control system. Usually, the task of the Identification of Human activities is mapped to the classification task of images representing a person’s actions. This Project used for human activities’ classification using machine learning methods such as CNN. This Project provides the results to Identification of Human activities task using the set of images representing five different categories of daily life activities. The usage of images also webcam to find out the live activities of the users that could improve the classification results of Identification of Human activities is beyond the scope of this research.
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