EDGE-BASED VIDEO PROCESSING ON RASPBERRY PI

Authors

  • Mr. Nagesh Nam,Mr. Sukumar N Author

DOI:

https://doi.org/10.48047/wz3gxb87

Keywords:

Edge Computing, Raspberry Pi, Embedded Video Processing, Motion Detection, Face Recognition, Hand Detection, OpenCV, Lightweight Deep Learning, Smart Surveillance, IoT-enabled Vision Systems

Abstract

intelligent video analytics at the edge. This paper focuses on the study and implementation of various methods for motion detection, face recognition, and hand detection using state-of-the-art computer visionalgorithms, optimized for the Raspberry Pi platform. By leveraging OpenCV functions and custom-trained classifiers, the system is designed to operate

Downloads

Download data is not yet available.

Downloads

Published

15.11.2022

Issue

Vol. 12 No. 4 (2022): volume 12 issue 4(2022)

Section

Articles

License

You are free to:

  1. Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
  2. Adapt — remix, transform, and build upon the material for any purpose, even commercially.
  3. The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

  1. Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
  2. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Notices:

You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .

No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

How to Cite

EDGE-BASED VIDEO PROCESSING ON RASPBERRY PI. (2022). International Journal of Information and Electronics Engineering, 12(4), 80-85. https://doi.org/10.48047/wz3gxb87