Pipelogic

Track Objects (Hybrid SORT)

Hybrid-SORT multi-object tracker over per-frame [BoundingBox] or [Segmentation]. It extends observation-centric SORT with weak cues - a confidence-state score and a velocity-direction term - so heavily overlapping boxes in a crowd are still told apart. A Kalman motion model plus class-aware gating give stable ids. Emits one active-track list per frame, not per box.

Track Objects (ByteTrack)

ByteTrack multi-object tracker over per-frame [BoundingBox] or [Segmentation]. Its two-stage association keeps low-confidence detections instead of discarding them, recovering objects through occlusion. A Kalman motion model plus class-aware gating give stable ids. Emits one active-track list per frame, not per box.

Track Objects (OC SORT)

OC-SORT multi-object tracker over per-frame [BoundingBox] or [Segmentation]. Observation-centric: when a track is re-observed after occlusion its Kalman filter is re-updated along the trajectory between observations, and observation momentum keeps headings consistent, so ids survive the gap. Motion-only, no appearance model. Emits one active-track list per frame, not per box.

Summarize Tracked Object

Per-track Bayesian classifier stabiliser. Reads per-frame class [Double] probabilities tagged with a track id, blends them over a sliding history weighted by confidence and prior, and emits oneof t[[(UInt64, UInt64, Bool)], [Observation.Event]].

Track Objects (BoT SORT)

BoT-SORT multi-object tracker over per-frame [BoundingBox] or [Segmentation]. A ByteTrack-style two-stage IoU association keeps low-confidence detections instead of discarding them, a Kalman motion model predicts each track, and a per-frame camera-motion estimate warps prior boxes so global camera movement does not break the match. Emits one active-track list per frame, not per box.

Track Objects (BoostTrack)

BoostTrack multi-object tracker over per-frame [BoundingBox] or [Segmentation]. A SORT-family Kalman tracker that boosts detection confidence and inflates soft-BIoU overlap before association, so weak detections in crowded scenes survive and keep their ids. Class-aware gating gives stable ids. Emits one active-track list per frame, not per box.