Project in one sentence
Adapt Depth Anything V3 Small to an 8 GB Jetson Orin Nano Super for incremental multi-view point-cloud reconstruction with overlapping windows.
Research question
How effectively can Depth Anything V3 Small be adapted for incremental, spatially coherent point-cloud reconstruction on an 8 GB edge device?
Architecture
calibrated RGB camera
→ slow, overlapping frame selection
→ 4-frame DA3 window with 2 retained overlap frames
→ relative depth + confidence + intrinsics + camera poses
→ confidence-filtered window point cloud
→ overlap-based Sim(3) alignment
→ bounded global point cloud
→ live viewer and exportLocked defaults
- Model:
depth-anything/DA3-SMALL - Runtime: official Python API with PyTorch FP16
- Primary configuration: 4 frames, 2-frame overlap, 336 px
- Fallback: 3 frames, 2-frame overlap, 280 px
- Memory gate: peak used memory below 7.0 GB
- Confidence filter: discard the lowest 40% per frame
- Map bounds: 30 accepted windows and 1,000,000 points
- Live target: one accepted viewer update every five seconds
- Scale: arbitrary internal units until an independent 1.0 m reference is applied
Project notes
Proposal
- Capstone Proposal — submission-ready motivation, objectives, tiers, and success criteria
- Risks and Limitations — scale, alignment, deployment, validity, and scope risks
Design
- System Architecture — data flow, sliding-window state, queues, and runtime artifacts
- DA3 Model and Outputs — checkpoint, inference configuration, output contract, and coordinates
- Window Alignment and Mapping — Sim(3) registration, point accumulation, bounds, and metric scaling
- Final Demo Target and Reference Systems — achievable visual outcome, related projects, and explicit stretch goals
Implementation
- Jetson Platform and Feasibility — hardware budget, dependency compatibility, and feasibility decision
- Camera and Data Collection — calibration, capture settings, recordings, and scale reference
- Deployment Roadmap — ordered phases, implementation gates, and deliverables
Evaluation
- Evaluation Plan — evaluation questions, locked test configuration, and acceptance summary
- Test Protocols — step-by-step resource, geometry, alignment, performance, and stability tests
- Results Templates — tables, required figures, and reporting guidance
Milestones
- Freeze the Jetson software stack and camera mode
- Calibrate the camera below 0.5 px mean reprojection error
- Pass the DA3 Small resource-feasibility gate
- Validate DA3 output shapes and coordinate conventions
- Export a confidence-filtered point cloud from one window
- Align two recorded windows with Sim(3)
- Accumulate a bounded recorded room sweep
- Integrate live capture and continual viewer updates
- Apply independent scale normalization and measure the doorway
- Complete the five-minute performance test
- Complete the 15-minute stability run