feat: initialize offline multiview pose tracking experiment

Set up pose_tracking_exp as a uv-managed Python package for offline multiview body tracking experiments.

This initial commit includes:

- the typed package scaffold, CLI entrypoints, and repo-local uv configuration

- scene and replay loaders for generic JSON replays and ActualTest parquet inputs

- ParaJumping payload conversion and RTMPose-to-body20 normalization

- a custom articulated tracker with tentative, active, and lost lifecycle handling

- RPT-backed proposal generation, camera convention handling, and multiview reprojection updates

- regression tests for normalization, camera conventions, ActualTest ingestion, seeding, and tracker smoke flows

- project documentation covering extrinsic formats and the ActualTest calibration caveat

README.md

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+# pose_tracking_exp
+
+Offline multiview body tracking experiments built around:
+
+- `RapidPoseTriangulation` for geometric birth proposals
+- a typed replay format for recorded per-camera detections
+- a recursive active/lost tracker with fixed bone lengths
+
+## Install
+
+```bash
+uv sync --extra dev
+```
+
+## Run
+
+```bash
+uv run pose-tracking-exp run data/scene.json data/replay.jsonl
+```
+
+`scene.json` may declare camera extrinsics in either format:
+
+- `opencv_world_to_camera`: OpenCV `solvePnP` / `cv2.projectPoints` convention. This is the default.
+- `rpt_camera_pose`: camera pose in world coordinates, which is what `RapidPoseTriangulation` expects internally.
+
+The loader normalizes both to OpenCV extrinsics for reprojection and converts to RPT pose only when building the triangulation config.
+If you already have an older hand-authored scene file that stored RPT camera pose directly, set `extrinsic_format` explicitly to `rpt_camera_pose`.
+
+## Convert ParaJumping Payload Records
+
+```bash
+uv run pose-tracking-exp convert-parajumping input.jsonl output.jsonl
+```
+
+## ActualTest Calibration Caveat
+
+`ActualTest_WeiHua/camera_params.parquet` appears to store raw OpenCV extrinsics from the ChArUco pipeline, not camera poses. The tracker now converts those values before calling `RapidPoseTriangulation`, because RPT expects camera centers and camera-to-world rotation.
+
+In repo terms:
+
+- OpenCV reprojection keeps `R`, `T`, and `rvec` as world-to-camera extrinsics.
+- RPT export uses the derived camera pose `pose_R = R^T` and `pose_T = -R^T t`.
+
+There is still one upstream caveat: the ParaJumping calibration notebook averages `rvec` samples component-wise before writing the parquet. That is a rough approximation for rotations and can introduce some bias even when the convention is handled correctly.