NavVis | Blog | BUILD BETTER REALITY

NavVis Is Changing How Point Clouds are Visualized. Here’s Why and How

Written by Tim Runge | Feb 11, 2026

Reality capture is now embedded in the daily workflows of many organizations. Teams scan more frequently, in more detail, and at larger scale.

NavVis sees this reflected in the amount of data customers send through NavVis IVION, which totals several petabytes processed in recent years and hundreds of terabytes hosted at any moment.

As this activity grows, a shared challenge emerges: Point clouds become more difficult to read when multiple passes, sessions, or rescans overlap.

This isn’t a technical failure. It’s simply a natural outcome of how real environments are documented. But it does shape how easily teams can understand and use the data.

Why multiple captures reduce point cloud clarity

Multiple passes through the same space help create fuller coverage and better geometry. They also introduce visual side effects:

  • soft or duplicated edges
  • ghosting from reflective surfaces
  • clusters of points from earlier captures
  • older geometry still visible after changes onsite

For teams working in construction, facility planning , or long-term operations, these effects accumulate over time. The dataset becomes harder to interpret, and distinguishing current conditions from earlier scans requires additional effort.

How NavVis IVION handles overlaps and repeated scans

Recurring scans are now common across industries. Construction teams document progress weekly. Facility teams scan areas after each layout changes. Industrial sites capture updates to support long-term asset management.

As these datasets accumulate, older and newer scans can blend in ways that complicate interpretation. A door may appear in two positions. A piece of equipment can show up even though it was removed. A ceiling can look doubled because geometry from a previous scan remains visible.

NavVis IVION is designed to support this growing need for clarity and offers two built-in functions that help present point clouds in a clearer, more useful way, even when they contain heavy overlaps or repeated sessions: Hide Overlap and Point Cloud Cleanup.

Hide Overlap: hiding redundant and outdated scans automatically

Hide Overlap evaluates the point cloud voxel by voxel, identifying which dataset provides the strongest representation for each area. Points from other datasets are hidden rather than deleted.

This results in a cleaner, more legible point cloud:

  • surfaces appear sharper
  • small details become easier to read
  • ghost points and duplicate geometry are significantly reduced

Hide Overlap also supports partial rescans. When only a portion of a site has changed, teams can capture just that area. NavVis IVION then prioritizes the newer scan where it overlaps with older data, displaying the point clouds and panoramas that best reflect the current state of the environment.

This reduces unnecessary fieldwork and helps keep digital representations up to date.


Point Cloud Cleanup: Targeted refinements in the browser

Some adjustments require direct control. Temporary equipment, scaffolding, or isolated points from reflective surfaces can create confusion during review.

Point Cloud Cleanup allows teams to make these corrections directly in NavVis IVION:

  • select and remove points or regions
  • undo changes at any time
  • preserve original data unless intentionally saved

This avoids the need to export large point clouds into external tools and helps teams maintain a single, consistent dataset.

A platform built for a more data-driven industry

As spatial data becomes a foundation for planning, operations, and verification, many organizations are adopting workflows that depend on better spatial awareness: understanding conditions across sites, comparing them over time, and making decisions with greater transparency and control.

Clean, comprehensible point clouds are essential for this shift.

Hide Overlap and Point Cloud Cleanup reflect how NavVis IVION supports this evolution. They reduce clutter, simplify recurring updates, and help organizations trust the data they rely on.

And as scanning grows within industries seeking predictability, accountability, and smoother coordination, these capabilities help ensure that spatial data serves as a dependable reference across teams.