Fast and Economical Object Tracking using Raspberry Pi 3.0
Purnima Prakas1, T.J Nagalakshmi2
1Purnima Prakas, Department of ECE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.
2T.J Nagalakshmi, Department of ECE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.
Manuscript received on 16 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 06 September 2019 | PP: 336-338 | Volume-8 Issue- 6S, August 2019 | Retrieval Number: F10700886S19/19©BEIESP | DOI: 10.35940/ijeat.F1070.0886S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper proposes a way to construct a financially cheap and fast object tracking using Raspberry Pi3. Multiple object detection is an important step in any computer vision application. Since the number of cameras included is more these gadgets are compelled by expense per hub, control utilization and handling power. We propose a tracking system with low power consumption. The framework is completely designed with python and OpenCV. The tracking quality and accuracy is measured using publicly available datasets.
Keywords: Cameras, Computer Vision, Python, Raspberry Pi, Pi camera, Tracking.
Scope of the Article: Computer Vision