Real-Time Object Detection using Deep Learning and Open CV
P. Devaki1, S. Shivavarsha2, G. Bala Kowsalya3, M. Manjupavithraa4, E.A. Vima5
1Dr. P. Devaki, Professor, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2S. Shivavarsha, UG Final Year, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3G. Bala Kowsalya, UG Final Year, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
4M. Manjupavithraa, UG Final Year, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
5E.A. Vima, Associate Professor, Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 07 October 2019 | Revised Manuscript received on 21 October 2019 | Manuscript Published on 26 December 2019 | PP: 411-414 | Volume-8 Issue-12S October 2019 | Retrieval Number: L110310812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1103.10812S19
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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: The object detection is used in almost every real-world application such as autonomous traversal, visual system, face detection and even more. This paper aims at applying object detection technique to assist visually impaired people. It helps visually impaired people to know about the objects around them to enable them to walk free. A prototype has been implemented on a Raspberry PI 3 using OpenCV libraries, and satisfactory performance is achieved. In this paper, detailed review has been carried out on object detection using region – conventionaal neural network (RCNN) based learning systems for a real-world application. This paper explores the various process of detecting objects using various object detections methods and walks through detection including a deep neural network for SSD implemented using Caffe model.
Keywords: Object Detection, RCNN, SSD, Caffe Model, Open CV Libraries, Neural Networks.
Scope of the Article: Deep Learning