Analysis to feature-based video stabilization/registration techniques within application of traffic data collection

Mojtaba T. Sadat; Francesco Viti

doi:10.1117/12.2180595

14 February 2015 Analysis to feature-based video stabilization/registration techniques within application of traffic data collection

Mojtaba T. Sadat, Francesco Viti

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Proceedings Volume 9445, Seventh International Conference on Machine Vision (ICMV 2014); 94451D (2015) https://doi.org/10.1117/12.2180595
Event: Seventh International Conference on Machine Vision (ICMV 2014), 2014, Milan, Italy

Abstract

Machine vision is rapidly gaining popularity in the field of Intelligent Transportation Systems. In particular, 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 examine the impact of multiple feature-based techniques for stabilization, and we show that SURF detector outperforms the others in terms of time efficiency and output similarity.

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Mojtaba T. Sadat and Francesco Viti "Analysis to feature-based video stabilization/registration techniques within application of traffic data collection", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94451D (14 February 2015); https://doi.org/10.1117/12.2180595

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KEYWORDS

Video

Sensors

Cameras

Motion estimation

Motion models

Corner detection

Intelligence systems

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