1. 1/5G. Silveira, “State-of-the-art Solutions for Vision-based Estimation” -
State-of-the-art Solutions for
Vision-based Estimation
Geraldo Silveira, PhD
Geraldo.Silveira@cti.gov.br

2. 2/5G. Silveira, “State-of-the-art Solutions for Vision-based Estimation” -
Problem Statement
• Vision-based estimation of
parameters that best describe a
phenomenon of interest
• Performance requirements: high
accuracy, fast response and
robustness to lighting changes
• Applications in 3D mapping,
augmented reality, visual
tracking, pose estimation, etc.
Example: Estimate motion
of a beating heart

3. 3/5G. Silveira, “State-of-the-art Solutions for Vision-based Estimation” -
Existing Methods

are not robust to arbitrary illumination changes; or

require particular image features; or

require particular objects; or

require particular cameras; or

require particular camera-object situations; or

require off-line learning steps; or

require relatively slow camera motion

4. 4/5G. Silveira, “State-of-the-art Solutions for Vision-based Estimation” -
State-of-the-art Solution

We have proposed a vision-based estimation solution which
– is highly accurate: all possible visual information is exploited;
no need of particular image features (e.g., points, lines, etc.)
– is versatile: works regardless of object shape, of camera motion
and of camera type (e.g., standard and omni cameras)
– is robust to arbitrary illumination changes and to aberrant
measures (e.g., occlusions)
– has large domain and rate of convergence; starts immediately
after task definition; no off-line learning steps
Further information can be obtained upon request

5. 5/5G. Silveira, “State-of-the-art Solutions for Vision-based Estimation” -
Application: Image Stabilization

Experimental setup
– a fully uncalibrated conventional camera
– completely unknown illumination conditions
– a freely moving object of unknown dimensions

Typical result
Region to be tracked and stabilized Some excerpts of the experiment