We continue to release after each development sprint. So here is our new release with three new features.
- Added individual resolutions per dimension.
- Automatic correction of integration truncation when value is too low.
- Added
gradient_step_fact parameter to control the smoothness of neighboring normals.
Adjusting resolutions per dimension will allow you to add more detail into dimension that require it (think about relief scans or similar non-square volumes). To adjust the settings look at the packaged configuration files that ship with ReconstructMe. Backward compatibility to older configuration files is broken, please update accordingly.
The second feature allows to detect misconfigurations of the integrate_truncation parameter. This parameter depends on the volume size and resolution. If a value below the minimum is detected, the truncation is clamped to the minimum value.
Below is screenshot of a high resolution keyboard and hand scan.
Here’s the configuration
camera_size_x: 640
camera_size_y: 480
camera_fx: 571.26
camera_fy: 571.26
camera_px: 320
camera_py: 240
camera_near: 100
camera_far: 2000
volume_size {
x: 1024
y: 1024
z: 128
}
volume_min {
x: -250
y: -250
z: 400
}
volume_max {
x: 250
y: 250
z: 600
}
integrate_truncation: 5
integrate_max_weight: 64
icp_max_iter: 20
icp_max_dist2: 200
icp_min_cos_angle: 0.9
smooth_normals: false
disable_optimizations: false
extract_step_fact: 0.5
gradient_step_fact: 0.5
Nikolas Früh dropped us a note that he finished his Master’s thesis. His thesis is all about measuring the building progress and incorporating that data into various processes. It is written in German language an contains around 15 pages dealing with ReconstructMe. ReconstructMe is compared to competitors in terms of usage and accuracy. Nikolas was so kind to allow us to publicly link his thesis for interested users. You can find it on the references page.
