Point Cloud bandwidth optimization (ROI and Downsampling) #6

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opened 2026-03-24 20:44:58 +00:00 by cristhian · 0 comments
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What is missing: The 3D output (point_cloud) is currently too large for efficient routing in complex dataflows, especially when multiple cameras are used or when the network is a bottleneck.

Where: Data processing and output logic.

Observable effect: Users can toggle between FULL, HALF, and ROI (Region of Interest) modes. In ROI mode, the point cloud size is reduced by ~90%, as the node only emits 3D data for the specific volumes where objects have been detected.

**What is missing:** The 3D output (`point_cloud`) is currently too large for efficient routing in complex dataflows, especially when multiple cameras are used or when the network is a bottleneck. **Where:** Data processing and output logic. **Observable effect:** Users can toggle between `FULL`, `HALF`, and `ROI` (Region of Interest) modes. In `ROI` mode, the point cloud size is reduced by ~90%, as the node only emits 3D data for the specific volumes where objects have been detected.
cristhian added this to the v0.1.0 - Reusable Vision Engine milestone 2026-03-24 20:44:58 +00:00
cristhian added the feature label 2026-03-24 20:45:13 +00:00
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