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# Homework 01: Survey & Design of 3D Multi-view Human Pose Estimation System
调研现有的多视角单人 (multiple view of single person) 多视角多人 (multi-view multi-person)
人体姿态估计系统/管线
## 参考答案
AI 生成的架构图, 不代表我此刻的实际想法, which changes every moment.
```mermaid
flowchart TD
%% =========================
%% Multi-view 2D stage
%% =========================
subgraph VIEWS["Per-view input (cameras 1..N)"]
direction LR
C1["Cam 1\n2D detections: 133×2 (+conf)"] --> T1["2D latest tracking cache\n(view 1)"]
C2["Cam 2\n2D detections: 133×2 (+conf)"] --> T2["2D latest tracking cache\n(view 2)"]
C3["Cam 3\n2D detections: 133×2 (+conf)"] --> T3["2D latest tracking cache\n(view 3)"]
C4["Cam 4\n2D detections: 133×2 (+conf)"] --> T4["2D latest tracking cache\n(view 4)"]
end
%% =========================
%% Cross-view association
%% =========================
subgraph ASSOC["Cross-view data association (epipolar)"]
direction TB
EPI["Epipolar constraint\n(Sampson / point-to-epiline)"]:::core
CYCLE["Cycle consistency / view-graph pruning"]:::core
GROUP["Assemble per-target multi-view observation set\n{view_id → 133×2}"]:::core
EPI --> CYCLE --> GROUP
end
T1 --> EPI
T2 --> EPI
T3 --> EPI
T4 --> EPI
%% =========================
%% Geometry / lifting
%% =========================
subgraph GEOM["3D measurement construction"]
direction TB
RT["Camera models\nK, [R|t], SO(3)/SE(3)"]:::meta
DLT["DLT / triangulation (init)"]:::core
NN["Optional NN lifting / completion"]:::core
BA["Optional reprojection refinement\n(1–5 iters)"]:::core
Y["3D measurement y(t)\nJ×3 positions (+quality / R / cov)"]:::out
RT --> DLT --> NN --> BA --> Y
end
GROUP --> DLT
%% =========================
%% Tracking filter + lifecycle
%% =========================
subgraph FILTER["Tracking filter (per target)"]
direction TB
GATE["Gating\n(Mahalanobis / per-joint + global)"]:::core
IMM["IMM (motion model bank)\n(CV/CA or low/med/high Q)"]:::core
PRED["Predict\nΔt, self-propagate"]:::core
UPD["Update\nKF (linear)\nstate: [p(3J), v(3J)]"]:::core
MISS["Miss handling & track lifecycle\n(tentative → confirmed → deleted)"]:::meta
GATE --> IMM --> PRED --> UPD --> MISS
end
Y --> GATE
%% Optional inertial fusion
IMU["IMU (optional)"]:::meta --> INERT["EKF/UKF branch (optional)\nwhen augmenting state with orientation"]:::meta --> IMM
%% =========================
%% IK + optional feedback
%% =========================
subgraph IKSTAGE["IK stage (constraint / anatomy)"]
direction TB
IK["IK optimization target\n(minimize joint position error,\nadd bone length / joint limits)"]:::core
FB["Optional feedback to filter\npseudo-measurement z_IK with large R"]:::meta
IK --> FB
end
UPD --> IK
FB -.-> GATE
%% =========================
%% SMPL / mesh fitting
%% =========================
subgraph SMPLSTAGE["SMPL / SMPL-X fitting"]
direction TB
VP["VPoser / pose prior"]:::core
SMPL["SMPL(θ, β, root)\nfit to joints / reprojection"]:::core
JR["JR: Joint Regressor\nmesh → joints (loop closure)"]:::core
OUT["Outputs\nmesh + joints + pose params"]:::out
VP --> SMPL --> JR --> OUT
JR -. residual / reproject .-> SMPL
end
IK --> SMPL
classDef core fill:#0b1020,stroke:#5eead4,color:#e5e7eb,stroke-width:1.2px;
classDef meta fill:#111827,stroke:#93c5fd,color:#e5e7eb,stroke-dasharray: 4 3;
classDef out fill:#052e2b,stroke:#34d399,color:#ecfeff,stroke-width:1.4px;
```
如果图片不能正确预览, 见 [fig/fig.svg](fig/fig.svg)

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flowchart TD
%% =========================
%% Multi-view 2D stage
%% =========================
subgraph VIEWS["Per-view input (cameras 1..N)"]
direction LR
C1["Cam 1\n2D detections: 133×2 (+conf)"] --> T1["2D latest tracking cache\n(view 1)"]
C2["Cam 2\n2D detections: 133×2 (+conf)"] --> T2["2D latest tracking cache\n(view 2)"]
C3["Cam 3\n2D detections: 133×2 (+conf)"] --> T3["2D latest tracking cache\n(view 3)"]
C4["Cam 4\n2D detections: 133×2 (+conf)"] --> T4["2D latest tracking cache\n(view 4)"]
end
%% =========================
%% Cross-view association
%% =========================
subgraph ASSOC["Cross-view data association (epipolar)"]
direction TB
EPI["Epipolar constraint\n(Sampson / point-to-epiline)"]:::core
CYCLE["Cycle consistency / view-graph pruning"]:::core
GROUP["Assemble per-target multi-view observation set\n{view_id → 133×2}"]:::core
EPI --> CYCLE --> GROUP
end
T1 --> EPI
T2 --> EPI
T3 --> EPI
T4 --> EPI
%% =========================
%% Geometry / lifting
%% =========================
subgraph GEOM["3D measurement construction"]
direction TB
RT["Camera models\nK, [R|t], SO(3)/SE(3)"]:::meta
DLT["DLT / triangulation (init)"]:::core
NN["Optional NN lifting / completion"]:::core
BA["Optional reprojection refinement\n(1–5 iters)"]:::core
Y["3D measurement y(t)\nJ×3 positions (+quality / R / cov)"]:::out
RT --> DLT --> NN --> BA --> Y
end
GROUP --> DLT
%% =========================
%% Tracking filter + lifecycle
%% =========================
subgraph FILTER["Tracking filter (per target)"]
direction TB
GATE["Gating\n(Mahalanobis / per-joint + global)"]:::core
IMM["IMM (motion model bank)\n(CV/CA or low/med/high Q)"]:::core
PRED["Predict\nΔt, self-propagate"]:::core
UPD["Update\nKF (linear)\nstate: [p(3J), v(3J)]"]:::core
MISS["Miss handling & track lifecycle\n(tentative → confirmed → deleted)"]:::meta
GATE --> IMM --> PRED --> UPD --> MISS
end
Y --> GATE
%% Optional inertial fusion
IMU["IMU (optional)"]:::meta --> INERT["EKF/UKF branch (optional)\nwhen augmenting state with orientation"]:::meta --> IMM
%% =========================
%% IK + optional feedback
%% =========================
subgraph IKSTAGE["IK stage (constraint / anatomy)"]
direction TB
IK["IK optimization target\n(minimize joint position error,\nadd bone length / joint limits)"]:::core
FB["Optional feedback to filter\npseudo-measurement z_IK with large R"]:::meta
IK --> FB
end
UPD --> IK
FB -.-> GATE
%% =========================
%% SMPL / mesh fitting
%% =========================
subgraph SMPLSTAGE["SMPL / SMPL-X fitting"]
direction TB
VP["VPoser / pose prior"]:::core
SMPL["SMPL(θ, β, root)\nfit to joints / reprojection"]:::core
JR["JR: Joint Regressor\nmesh → joints (loop closure)"]:::core
OUT["Outputs\nmesh + joints + pose params"]:::out
VP --> SMPL --> JR --> OUT
JR -. residual / reproject .-> SMPL
end
IK --> SMPL
classDef core fill:#0b1020,stroke:#5eead4,color:#e5e7eb,stroke-width:1.2px;
classDef meta fill:#111827,stroke:#93c5fd,color:#e5e7eb,stroke-dasharray: 4 3;
classDef out fill:#052e2b,stroke:#34d399,color:#ecfeff,stroke-width:1.4px;

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