Analysis to Feature-Based Video Stabilization/Registration Techniques within Application of Traffic Data Collection

Tafaghod Sadat Zadeh, Seyed Mojtaba; Viti, Francesco

Reference : Analysis to Feature-Based Video Stabilization/Registration Techniques within Applicat...


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/19566

Title :	Analysis to Feature-Based Video Stabilization/Registration Techniques within Application of Traffic Data Collection
Language :	English
Author, co-author :	Tafaghod Sadat Zadeh, Seyed Mojtaba [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
	Viti, Francesco [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit >]
Publication date :	2015
Main document title :	Proceedings of the ICMV Conference
Peer reviewed :	Yes
Audience :	International
Event name :	7th International Conference on Machine Vision
Event date :	19-21 November 2014
Event organizer :	Science and Engineering Insititute (SCIEI)
Event place (city) :	Milan
Event country :	Italy
Keywords :	[en] Video Stabilization ; Image Registration
Abstract :	[en] Machine vision is rapidly gaining popularity in various applications, among others in the field of Intelligent Transportation Systems. In particular, potential advantages are foreseen by the exploitation of Aerial Vehicles (AV) in delivering a superior view on traffic phenomena. However, vibration on AVs makes it difficult to extract moving objects on the ground. To partly overcome this issue, image stabilization/registration procedures are adopted to correct and stitch multiple frames taken of the same scene but from different positions, angles, or sensors. In this study, we aim to examine the impact of multiple feature-based techniques for video stabilization using different scenarios. In the proposed framework, SURF detector outperformed the others in terms of time efficiency and output similarity.
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/19566

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