Oriental Journal of Computer Science and Technology

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Human Activity Recognition System


Affiliations
1 Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India
 

Modern human activity recognition systems are mainly trained and used upon video stream and images data that understand the features and actions variations in the data having similar or related movements. Human Activity Recognition plays a significant role in human-to-human and human-computer interaction. Manually driven system are highly time consuming and costlier. In this project, we aim at designing a cost-effective and faster Human Activity Recognition System which can process both video and image in order to recognize the activity being performed in it, thereby aiding the end user in various applications like surveillance, aiding purpose etc. This system will not only be cost effective but also as a utility-based system that can be incorporated in a large number of applications that will save time and aid in various activities that require recognition process, and save a lot of time with good accuracy Also, it will aid the blind people in availing the knowledge of their surroundings.

Keywords

Deep Learning; Neural Network.
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  • Human Activity Recognition System

Abstract Views: 219  |  PDF Views: 1

Authors

Pankaj Bhambri
Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India
Harpreet Kaur
Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India
Akarshit Gupta
Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India
Jaskaran Singh
Department of Information Technology, Guru Nanak Dev Engineering College, Ludhiana, India

Abstract


Modern human activity recognition systems are mainly trained and used upon video stream and images data that understand the features and actions variations in the data having similar or related movements. Human Activity Recognition plays a significant role in human-to-human and human-computer interaction. Manually driven system are highly time consuming and costlier. In this project, we aim at designing a cost-effective and faster Human Activity Recognition System which can process both video and image in order to recognize the activity being performed in it, thereby aiding the end user in various applications like surveillance, aiding purpose etc. This system will not only be cost effective but also as a utility-based system that can be incorporated in a large number of applications that will save time and aid in various activities that require recognition process, and save a lot of time with good accuracy Also, it will aid the blind people in availing the knowledge of their surroundings.

Keywords


Deep Learning; Neural Network.

References





DOI: https://doi.org/10.13005/ojcst13.0203.05