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Machine Vision and Applications

, Volume 25, Issue 5, pp 1283–1308 | Cite as

HMPMR strategy for real-time tracking in aerial images, using direct methods

  • Carol MartínezEmail author
  • Pascual Campoy
  • Iván F. Mondragón
  • José Luis Sánchez-Lopez
  • Miguel A. Olivares-Méndez
Original Paper

Abstract

The vast majority of approaches make use of features to track objects. In this paper, we address the tracking problem with a tracking-by-registration strategy based on direct methods. We propose a hierarchical strategy in terms of image resolution and number of parameters estimated in each resolution, that allows direct methods to be applied in demanding real-time visual-tracking applications. We have called this strategy the Hierarchical Multi-Parametric and Multi-Resolution strategy (HMPMR). The Inverse Composition Image Alignment Algorithm (ICIA) is used as an image registration technique and is extended to an HMPMR-ICIA. The proposed strategy is tested with different datasets and also with image data from real flight tests using an Unmanned Aerial Vehicle, where the requirements of direct methods are easily unsatisfied (e.g. vehicle vibrations). Results show that using an HMPMR approach, it is possible to cope with the efficiency problem and with the small motion constraint of direct methods, conducting the tracking task at real-time frame rates and obtaining a performance that is comparable to, or even better than, the one obtained with the other algorithms that were analyzed.

Keywords

Visual tracking Image registration  Hierarchical methods UAVs Parametric motion 

Notes

Acknowledgments

The work described in this paper is the result of several research stages conducted at the Computer Vision Group of the Universidad Politécnica de Madrid. The authors would like to thank the Universidad Politécnica de Madrid, the Consejería de Educación de la Comunidad de Madrid, and the Fondo Social Europeo (FSE) for the Ph.D. Scholarships of some of the Authors. This work has been supported by the Spanish Ministry of Science under grant MICYT DPI2010-20751-C02-01.

Supplementary material

Supplementary material 1 (mp4 48222 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Carol Martínez
    • 1
    Email author
  • Pascual Campoy
    • 1
  • Iván F. Mondragón
    • 2
  • José Luis Sánchez-Lopez
    • 1
  • Miguel A. Olivares-Méndez
    • 1
    • 3
  1. 1.Computer Vision GroupUniversidad Politécnica de Madrid, Centro de Automática y Robótica (CAR) UPM-CSICMadridSpain
  2. 2.Department of Industrial Engineering, Faculty of EngineeringPontificia Universidad JaverianaBogotá D.C.Colombia
  3. 3.Automation Research Group, Interdisciplinary Centre for Security, Reliability and Trust (SnT)University of LuxembourgLuxembourgLuxembourg

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