|
Showing 1 - 1 of
1 matches in All Departments
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.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.