The platform emerged from from the realization that an exact product like this does not exist yet and the ones that do are inefficient or expensive. This lead to fragmented workflows and tooling as well as inconsisten interfaces which slowed down critical engineering processes.
Challenges
The Problem
[02]
01
Fragmented Systems
Currently photogrammetry workflows and subsequent comparisons relied on disconnected tools with inconsistent workflows and duplicated operational overhead.
02
Poor Data Visibility
Scan and Comparison metrics lacked centralized visualization and actionable context.
Solutions
The Response
[02]
01
Unified Interface
A cohesive application that consolidates infrastructure tooling into one streamlined experience.
02
Real-Time Monitoring
Integrated statistical analysis provide immediate visibility into system performance and anomalies.
Try it yourself!
Interactive Demo
3D reconstruction
See how we can transform a simple smartphone video into a detailed 3D model.
Help
Loading Model
Rotate • Pan • Zoom
Format
GLB
Points
0
Render
WebGL
Interaction
Orbit Controls
01
Capture a Video
Record a smooth 30–60 second video around the object, ensuring that consecutive views overlap and all visible surfaces are captured.
Equipment: Any smartphone camera
Settings: 1080p, 30fps
Tips: Consistent lighting works best
Avoid motion blur
02
Frame Selection & Preprocessing
Frames are extracted from the video and filtered to keep only images that contribute new viewpoints while reducing redundancy and processing time.
Automatic frame sampling
Background removal
Image quality filtering
Reduced computational load
03
Feature Detection & Matching
Distinctive visual features are detected in each image and matched across multiple views, allowing the system to estimate camera positions and scene geometry.
Identify distinctive points on object
Match these features across frames
Estimate camera positions for each shot
Recover sparse scene structure
04
Sparse Reconstruction
Matched features are triangulated into a sparse 3D point cloud while camera positions are refined.
Structure-from-Motion
Sparse point cloud generation
Camera pose optimization
Initial scene geometry
05
Dense Reconstruction & Cleaning
Additional depth information is calculated across all images to generate a detailed dense point cloud, which is then cleaned to remove noise and outliers.
Multi-view stereo reconstruction
Millions of reconstructed points
Noise filtering
Outlier removal
Explore sparse, dense, and cleaned point cloud in the viewer above
06
Surface Reconstruction
The point cloud is converted into a continuous mesh, filling the gaps between points so the result is a solid, exportable surface
Poisson surface reconstruction algorithm
Smooth, watertight mesh
Ready for comparison or export
Now let's compare two objects...
Interactive Demo
3D comparison
See how we compare the created 3D model against a reference scan to measure geometric accuracy.
Help
Loading Model
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Median Error
The median point-to-cloud distance between the reference and the captured cloud.
2.5 mm
95th Percentile Error
95 % of points fall within this error margin - a robust upper bound for accuracy.
16.0 mm
RMSE
Root Mean Square Error. Penalises larger deviations more heavily than the median.
36.0 mm
Overlap
Share of reference points that have a near match in the scanned cloud
97.3 %
Points
0
01
Alignment
Before two scans can be compared, they need to share a coordinate system — this step rotates, scales, and positions them to match.
PCA-based initial alignment
ICP refinement for precision
Scaling and normalization across scans
02
Distance Analysis
Once aligned, the nearest geometric differences between the models are calculated to measure how far each region deviates from the reference.
Nearest-neighbor search
Point-to-surface distance computation
Deviation measurements
Error statistics generation
03
Visualization & Metrics
Measured deviations are visualized as a color-coded heatmap and summarized using quantitative accuracy metrics.
Point-to-point distance calculation
Creation of color-coded deviation heatmap
Gathering metrics like mean deviation or RMSE
Switch between the reference scan, the 3D model, and the comparison in the viewer above
Currently in development
Target Launch Q4 2026
This project is currently evolving through active iteration, system refinement, and interface testing. Additional features, technical insights, and launch details will be shared progressively.
Thank you for reading
CONTACT
Feel free to contact me with questions, offers or ideas.