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A Study on Computer Vision Systems for Real-Time Object Detection and Tracking

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Daniel Mohammed, Francis A. Amavi
10.5120/ijca2017915484

Daniel Mohammed and Francis A Amavi. A Study on Computer Vision Systems for Real-Time Object Detection and Tracking. International Journal of Computer Applications 175(3):24-27, October 2017. BibTeX

@article{10.5120/ijca2017915484,
	author = {Daniel Mohammed and Francis A. Amavi},
	title = {A Study on Computer Vision Systems for Real-Time Object Detection and Tracking},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2017},
	volume = {175},
	number = {3},
	month = {Oct},
	year = {2017},
	issn = {0975-8887},
	pages = {24-27},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume175/number3/28470-2017915484},
	doi = {10.5120/ijca2017915484},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Computer Vision (CV) concentrates on the automatic extraction, examination and comprehension of valuable data from a solitary image or a group of images. Object tracking, one of the key areas in CV has received a lot of attenstion in recent times. Tracking objects is a systematic process of monitoring the movement of a target object from its initial state to the nth state over a period of time using a camera. This technique is usually employed as a security feature in both military and civilian systems. However, prior studies has shown that tracking objects in motion is a very difficult task and is a hot research hotspot in the field of computer vision and machine learning. In this review paper we discuess various techniques in detection, tracking and some other related works of moving objects in video streams.

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Keywords

Automatic Extraction, Object Detection, Object Tracking, Computer Vision and Machine Learning.