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Real-Time Visual Tracking of 3D-Objects

  • Fabrizio Caccavale
  • Vincenzo Lippiello
  • Bruno Siciliano
  • Luigi Villani
Chapter
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 10)

Abstract

The use of visual sensors may have high impact in applications where it ist required to measure the pose (position and orientation) and the visual features of object moving in unstructured environments. In robotics, the measurement provided by video cameras can be directly used to perform closed-loop control of the robot end-effector pose. In this chapter the problem of real-time estimation of the position and orientation of a moving object using a fixed stereo camera system is considered. An approach based on the use of the Extended Kalman Filter (EKF) combined with a 3D representation of the objects geometry based on Binary Space Partition (BSP) trees ist illustrated. The performance of the proposed visual tracking algorithm is experimentally tested in the case of an object moving in the visible space of a fixed stereo camera system.

Keywords

Feature Point Selection Algorithm Extend Kalman Filter Visual Tracking Visual Servoing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Authors and Affiliations

  • Fabrizio Caccavale
    • 1
  • Vincenzo Lippiello
    • 2
  • Bruno Siciliano
    • 2
  • Luigi Villani
    • 2
  1. 1.Dipartimento di Informatica e Fisica dell’Ambiente, Università della Basilicata, Contrada Macchia Romana, 85100 PotenzaItaly
  2. 2.PRISMA Lab, Dipartimento di Informatica e Sistemistica, Università di Napoli “Federico II”, Via Claudio 21, 80125 NapoliItaly

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