Authors:
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (4 chapters)
-
Front Matter
About this book
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.
Authors and Affiliations
-
Blackmagic Design, Colorado Springs, USA
Joel Gibson
-
Department of Computer and Electrical Engineering, Florida Atlantic University, Boca Raton, USA
Oge Marques
Bibliographic Information
Book Title: Optical Flow and Trajectory Estimation Methods
Authors: Joel Gibson, Oge Marques
Series Title: SpringerBriefs in Computer Science
DOI: https://doi.org/10.1007/978-3-319-44941-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Author(s) 2016
Softcover ISBN: 978-3-319-44940-1Published: 09 September 2016
eBook ISBN: 978-3-319-44941-8Published: 01 September 2016
Series ISSN: 2191-5768
Series E-ISSN: 2191-5776
Edition Number: 1
Number of Pages: X, 49
Number of Illustrations: 6 b/w illustrations
Topics: Computer Imaging, Vision, Pattern Recognition and Graphics