multi fce stuff

docs/port-plan.md

@@ -2,7 +2,7 @@
 
 Self-contained. You should not need any prior conversation to execute this.
 
-**Implementation status (2026-09-28):** steps 0–9 are in. Step 6 reads extracted
+**Implementation status (2026-09-29):** steps 0–9 are in. Step 6 reads extracted
 footage, detects landmarks with local MediaPipe assets at full source cadence, and
 runs the same freeze path as the synthetic take. The scene time map can sample the
 frozen roto at a lower picture fps without changing source analysis, duration or
@@ -13,9 +13,24 @@ absence intervals through measurement and freeze. Step 9 adds the Django backend
 the three-tier split, content-addressed tier 2 with the detector version inside
 every key, leaf addressing for tier 1, and project load/save that round-trips.
 
-**Still open.** Step 8's parameter UI and scoped regeneration, and automatic
-per-feature detection. Everything under "Out, and do not build it" below, which
-step 9 did not touch.
+Step 8 now has parameter controls and scoped regeneration from retained source.
+Multi-face representation is complete: each tracked subject has a drawing
+timeline, placed by an ordinary symbol instance. See
+[multi-face representation](multi-face-representation.md) for the implemented
+model, verification and compatibility limits.
+
+**Next, in order:** commit the verified checkpoint; exercise real two-person
+footage, including crossings and disappearances; build performance-pose
+Suggest/Keep/Drop and instance-scoped picture rates; then add plate-drawing
+selection and independent tracing references. The
+[timing handoff](timing-handoff.md) records current code and implementation order.
+Reopen the representation only for a concrete requirement it cannot express.
+
+**Still open:** real-footage identity validation, automatic per-feature detection,
+the timing and tracing work above, and time-varying parameter settings. Older flat
+captures need reanalysis for the new regeneration path; no migration is included.
+The step descriptions below retain the original port scope; this status and the
+linked handoffs describe subsequent work.
 
 ## What arthur is
 
@@ -355,7 +370,7 @@ stencilled by the sclera.
 minus paint. The fixed pixel thresholds remain provisional; step 8 exposes their
 parameters for tuning without changing the source track or picture timing.
 
-### 8 — knobs
+### 8 — knobs — DONE for static settings and scoped regeneration
 Build the parameter model before its UI. Define each parameter once with its
 default, validation, applicable area and regeneration dependencies. Store values
 by stable subject and feature ID. Represent an eye pair as one group with one or
@@ -376,8 +391,9 @@ visible eye. This is an input format, not a control UI or an automatic detector.
 
 Use leaf-addressable settings under the clip, subject, feature and optional
 group. Retain source measurements so a setting change can regenerate affected
-channels without re-detecting footage. Time-varying parameter values and all
-parameter controls are deferred to the UI pass.
+channels without re-detecting footage. Static parameter controls and scoped
+regeneration are implemented for takes and composed stages. Time-varying
+parameter values remain deferred.
 
 ### 9 — backend — DONE
 Django project, the `clips` app, models for
@@ -431,7 +447,7 @@ nobody should pre-empt by porting the old one.
 
 ## Two things to not foreclose
 
-Feature controls will later handle more than one face and editing presence.
+Feature controls now handle more than one face; editing presence remains future work.
 The underlying identity, occlusion and group association model begins in step 8:
 
 - **Presence is not visibility.** An occluded feature has *no value* on a frame,
@@ -440,5 +456,6 @@ The underlying identity, occlusion and group association model begins in step 8:
 - **Params carry stable identity.** A subject and its features keep their IDs
   across observation gaps. A run of visible frames is not a new identity.
 
-The identity tracker, when it comes, should use the same pattern the iris and brow
-correspondences already use: vote across every frame rather than trusting one.
+The current identity tracker uses nearest-centroid assignment. Validate it on
+real crossings and disappearances before choosing a more elaborate policy; the
+iris and brow correspondence code offers whole-take voting as one option.