3D vision
3D vision guides
Laser profilers and 3D sensors: when height data beats a 2D image, and how to set them up.
3D vision · Troubleshooting
Stereo point cloud visualization: check missing XYZ points
Diagnose stereo point cloud visualization by checking valid-pixel counts, disparity scaling, XYZ units, export rows and viewer axis limits.
3D vision · Explainer
3D scanner prototype planning for limb surface capture
Plan a 3D scanner prototype for limb capture: define coverage, accuracy, scan time, calibration, motion limits and safe validation stages.
3D vision · Explainer
Visual servoing feature selection for perpendicular approach
Visual servoing feature selection explained: combine image centers, depth and surface normals to constrain centering and perpendicular approach.
3D vision · Troubleshooting
Stereo disparity map troubleshooting after rectification
Stereo disparity map troubleshooting: measure vertical alignment, verify image order and search range, and separate matching faults from depth errors.
3D vision · Explainer
Multi-camera point cloud synchronization for mobile robots
Separate multi-camera point cloud synchronization into exposure timing, clock alignment and calibration, with motion-error and bandwidth examples.
3D vision · Explainer
Bounding box depth: mapping image pixels to 3D points
Find bounding box depth from aligned images or organized point clouds, with checks for changing point counts, calibration, timing and invalid samples.
3D vision · Explainer
Wide baseline stereo camera selection for depth mapping
Wide baseline stereo camera selection explained with overlap, disparity, depth uncertainty, synchronization, bandwidth, and mounting checks.
3D vision · Explainer
Thermal RGB image fusion without losing temperature data
Register thermal and RGB views on building geometry, preserve radiometric values, and quantify parallax, resampling, and boundary uncertainty.
3D vision · Explainer
3D scanner prototype planning for limb surface capture
Plan a 3D scanner prototype for limb capture: define coverage, accuracy, scan time, calibration, motion limits and safe validation stages.
3D vision · Explainer
Visual servoing feature selection for perpendicular approach
Visual servoing feature selection explained: combine image centers, depth and surface normals to constrain centering and perpendicular approach.
3D vision · Troubleshooting
Stereo disparity map troubleshooting after rectification
Stereo disparity map troubleshooting: measure vertical alignment, verify image order and search range, and separate matching faults from depth errors.
3D vision · Explainer
Multi-camera point cloud synchronization for mobile robots
Separate multi-camera point cloud synchronization into exposure timing, clock alignment and calibration, with motion-error and bandwidth examples.
3D vision · Explainer
Bounding box depth: mapping image pixels to 3D points
Find bounding box depth from aligned images or organized point clouds, with checks for changing point counts, calibration, timing and invalid samples.
3D vision · Explainer
Wide baseline stereo camera selection for depth mapping
Wide baseline stereo camera selection explained with overlap, disparity, depth uncertainty, synchronization, bandwidth, and mounting checks.
3D vision · Explainer
Thermal RGB image fusion without losing temperature data
Register thermal and RGB views on building geometry, preserve radiometric values, and quantify parallax, resampling, and boundary uncertainty.
Shop: Cameras · All guides