© 2016

Optical Flow and Trajectory Estimation Methods


Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-x
  2. Joel Gibson, Oge Marques
    Pages 1-7
  3. Joel Gibson, Oge Marques
    Pages 9-23
  4. Joel Gibson, Oge Marques
    Pages 25-40
  5. Joel Gibson, Oge Marques
    Pages 41-49

About this book


This brief focuses on two main problems in the domain of optical flow and trajectory estimation: (i) The problem of finding convex optimization methods to apply sparsity to optical flow; and (ii) The problem of how to extend sparsity to improve trajectories in a computationally tractable way.

Beginning with a review of optical flow fundamentals, it discusses the commonly used flow estimation strategies and the advantages or shortcomings of each. The brief also introduces the concepts associated with sparsity including dictionaries and low rank matrices. Next, it provides context for optical flow and trajectory methods including algorithms, data sets, and performance measurement. The second half of the brief covers sparse regularization of total variation optical flow and robust low rank trajectories. The authors describe a new approach that uses partially-overlapping patches to accelerate the calculation and is implemented in a coarse-to-fine strategy. Experimental results show that combining total variation and a sparse constraint from a learned dictionary is more effective than employing total variation alone.

The brief is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to new researchers looking for cutting edge topics in optical flow as well as veterans of optical flow wishing to learn of the latest advances in multi-frame methods.


Optical flow Trajectory estimation Computer vision Sparsity Regularization Dictionary learning Video processing

Authors and affiliations

  1. 1.Blackmagic DesignColorado SpringsUSA
  2. 2.Department of Computer and Electrical EngineeringFlorida Atlantic UniversityBoca RatonUSA

Bibliographic information

  • Book Title Optical Flow and Trajectory Estimation Methods
  • Authors Joel Gibson
    Oge Marques
  • Series Title SpringerBriefs in Computer Science
  • Series Abbreviated Title SpringerBriefs Computer Sci.
  • DOI
  • Copyright Information The Author(s) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-3-319-44940-1
  • eBook ISBN 978-3-319-44941-8
  • Series ISSN 2191-5768
  • Series E-ISSN 2191-5776
  • Edition Number 1
  • Number of Pages X, 49
  • Number of Illustrations 6 b/w illustrations, 0 illustrations in colour
  • Topics Computer Imaging, Vision, Pattern Recognition and Graphics
  • Buy this book on publisher's site
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