Integrated 3D analysis of flight image sequences

  • Sanghoon Sull
  • Narendra Ahuja
Ego-Motion and 3D Recovery
Part of the Lecture Notes in Computer Science book series (LNCS, volume 800)


This paper is concerned with three-dimensional (3D) analysis of images showing 3D motion of an observer relative to a scene. It presents an approach to recovering 3D motion and structure parameters from multiple features present in a monocular image sequence such as points, regions, lines, texture gradient and vanishing line. For concreteness, the paper focuses on flight images of a planar, textured surface. In this paper, a linear integrated estimation method using two views is developed. Then, for robust estimation, a nonlinear integrated estimation method using multiple frames is presented. The integration of information in these diverse features is carried out using minimization of image errors. To reduce computation, a sequential-batch method is used to compute motion and structure. Performance is evaluated through simulations and experiments with a real image sequence digitized from a commercially available laserdisc of films taken from flying aircrafts.


Image Sequence Image Error Texture Gradient Defense Advance Research Project Agency Multiple Frame 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Sanghoon Sull
    • 1
  • Narendra Ahuja
    • 1
  1. 1.Beckman Institute and Coordinated Science LaboratoryUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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