Neural Processing Letters

, Volume 43, Issue 2, pp 459–477 | Cite as

Real-Time Model-Based Video Stabilization for Microaerial Vehicles

  • Wilbert G. Aguilar
  • Cecilio Angulo


The emerging branch of micro aerial vehicles (MAVs) has attracted a great interest for their indoor navigation capabilities, but they require a high quality video for tele-operated or autonomous tasks. A common problem of on-board video quality is the effect of undesired movements, so different approaches solve it with both mechanical stabilizers or video stabilizer software. Very few video stabilizer algorithms in the literature can be applied in real-time but they do not discriminate at all between intentional movements of the tele-operator and undesired ones. In this paper, a novel technique is introduced for real-time video stabilization with low computational cost, without generating false movements or decreasing the performance of the stabilized video sequence. Our proposal uses a combination of geometric transformations and outliers rejection to obtain a robust inter-frame motion estimation, and a Kalman filter based on an ANN learned model of the MAV that includes the control action for motion intention estimation.


Video stabilization Micro aerial vehicles Real-time RANSAC Modelling Motion intention Kalman filter 



This work has been partially supported by the Spanish Ministry of Economy and Competitiveness, through the PATRICIA Project (TIN 2012-38416-C03-01). The research fellow Wilbert G. Aguilar thanks the funding through a Grant from the Program “Convocatoria Abierta 2011” issued by the Secretary of Education, Science, Technology and Innovation SENESCYT of the Republic of Ecuador.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Automatic Control Department (ESAII)Universitat Politècnica de CatalunyaBarcelonaSpain

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