Refine an accepted region with local masks¶
Level: Optional extension · Strategy: Projection-domain segmentation
Segmentation is not required to create a semantic or spatial hypothesis. When a tighter outline is useful, open a transient gnomonic view centred on the accepted angular proposal and prompt a local segmenter.
Retain every candidate mask needed for audit. If a mask reaches a face edge, continue over overlapping neighbouring views, transfer the prior and fuse the accepted masks on the sphere. Release each RGB face and model embedding after evaluation; persist compact spherical masks and provenance rather than a cache of projected images.
Mask interpolation must be nearest-neighbour. Cross-face fusion must use explicit support and solid-angle overlap; a visually smooth overlay is not an independent correctness oracle.
Local refinement sequence¶
Centre a gnomonic face on the accepted proposal and choose a FOV that contains its uncertainty envelope.
Generate prompts from the proposal interior and exterior; keep the local model’s alternative masks and quality scores.
Backproject masks with nearest-neighbour sampling and clip them by face and source support.
If an accepted mask reaches a face border, open an overlapping face in that direction, transfer the prior and continue with a cycle/step limit.
Merge consistent masks with solid-angle IoU or containment, then compact the spherical masks and release transient RGB faces and embeddings.
Preserving alternatives is important: a locally plausible mask can represent one pipe, an entire pipe bank or background between them. A single attractive choice hides that uncertainty.
Segmentation refines spatial extent; it does not retroactively validate the semantic proxy or cross-view identity. Those remain separate evidence fields.
The Experimental facade and its limits are documented in the CAM and segmentation tutorial. Next: evaluate the result.