Motion estimation through efficient matching of a reduced number of reliable singular points

Blanco Adán, Carlos Roberto del ORCID: https://orcid.org/0000-0003-0618-3488, Jaureguizar Núñez, Fernando ORCID: https://orcid.org/0000-0001-6449-5151, Salgado Álvarez de Sotomayor, Luis ORCID: https://orcid.org/0000-0002-5364-9837 and García Santos, Narciso ORCID: https://orcid.org/0000-0002-0397-894X (2008). Motion estimation through efficient matching of a reduced number of reliable singular points. In: "IS&T / SPIE Electronic Imaging 2008", 28/01/2008-29/01/2008, San Jose, California (Estados Unidos). ISBN 978-0819469830. pp. 681102201-681102212. https://doi.org/10.1117/12.768125.

Description

Title: Motion estimation through efficient matching of a reduced number of reliable singular points
Author/s:
Item Type: Presentation at Congress or Conference (Article)
Event Title: IS&T / SPIE Electronic Imaging 2008
Event Dates: 28/01/2008-29/01/2008
Event Location: San Jose, California (Estados Unidos)
Title of Book: Real-Time Image Processing 2008: Proceedings of Electronic Imaging, Science and Technology
Date: 2008
ISBN: 978-0819469830
Subjects:
Freetext Keywords: Real Time, Motion Estimation, Singular Point, Noise Adaptive, Point descriptor, Point Matching
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Señales, Sistemas y Radiocomunicaciones
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Motion estimation in video sequences is a classical intensive computational task that is required for a wide range of applications. Many different methods have been proposed to reduce the computational complexity, but the achieved reduction is not enough to allow real time operation in a non-specialized hardware. In this paper an efficient selection of singular points for fast matching between consecutive images is presented, which allows to achieve real time operation. The selection of singular points lies in finding the image points that are robust to the noise and the aperture problem. This is accomplished by imposing restrictions related to the gradient magnitude and the cornerness. The neighborhood of each singular point is characterized by a complex descriptor vector, which presents a high robustness to illumination changes and small variations in the 3D camera viewpoint. The matching between singular points of consecutive images is performed by maximizing a similarity measure based on the previous descriptor vector. The set of correspondences yields a sparse motion vector field that accurately outlines the image motion. In order to demonstrate the efficiency of this approach, a video stabilization application has been developed, which uses the sparse motion vector field as input. Excellent results have been obtained in synthetic and real sequences, demonstrating the efficiency of the proposed motion estimation technique.

More information

Item ID: 3802
DC Identifier: https://oa.upm.es/3802/
OAI Identifier: oai:oa.upm.es:3802
DOI: 10.1117/12.768125
Deposited by: Memoria Investigacion
Deposited on: 21 Jul 2010 12:03
Last Modified: 20 Apr 2016 13:16
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