# Comparison Framework

## Selected Framework Type
Problem Diagnosis + Decision Support

## Selected Dimensions
1. VO Matcher Selection (functional correctness + performance)
2. Satellite Fine Matcher Maturity (production readiness)
3. Satellite Fine Matcher Accuracy (hit rate claims)
4. Model Loading Security (supply chain + CVEs)
5. VRAM Budget Accuracy
6. GTSAM Robustness (error handling)
7. Satellite Imagery Freshness (Ukraine-specific)

## Dimension Population

### 1. VO Matcher Selection

| Aspect | Draft04 (SuperPoint+LightGlue) | Proposed (XFeat) | Factual Basis |
|--------|-------------------------------|-------------------|---------------|
| Speed | 150-200ms/frame | ~15ms/frame | Fact #1, #3 |
| Quality (Megadepth AUC@10°) | ~50.1 (SuperPoint only) | 65.4 | Fact #2 |
| UAV VO validation | Not specific | SatLoc-Fusion 2025 | Fact #3 |
| VRAM | ~900MB (SP+LG) | ~200MB | Fact #15 |
| Regression intentional? | No — not in findings | N/A | Fact #1 |

### 2. Satellite Fine Matcher Maturity

| Aspect | LiteSAM | EfficientLoFTR (fallback) | Factual Basis |
|--------|---------|--------------------------|---------------|
| GitHub stars | 5 | 964 | Fact #5, #8 |
| Forks | 0 | many | Fact #5, #8 |
| License | None | Apache 2.0 | Fact #5, #8 |
| CVPR/top venue | MDPI Remote Sensing | CVPR 2024 | Fact #5, #8 |
| Independent reproduction | None found | Many | Fact #14 |
| HuggingFace | No | Yes | Fact #8 |
| ONNX support | No | No (but larger ecosystem) | Fact #9 |
| Parameters | 6.31M | 15.05M | Fact #5, #8 |

### 3. Satellite Fine Matcher Accuracy

| Aspect | LiteSAM | SuperPoint+LightGlue | Factual Basis |
|--------|---------|---------------------|---------------|
| UAV-VisLoc Hard HR | 61.65% | ~54-58% (est.) | Fact #4 |
| Self-made dataset Hard HR | 77.3% | ~58.3% (est.) | Fact #4 |
| RMSE@30 (UAV-VisLoc) | 17.86m | N/A | Fact #4 |
| Draft04 claim | "77.3% Hard HR" | — | Fact #4 (misrepresented) |

### 4. Model Loading Security

| Aspect | Current | Required | Factual Basis |
|--------|---------|----------|---------------|
| torch.load weights_only | Unspecified | Must use + PyTorch ≥2.10.0 | Fact #7 |
| LiteSAM weight integrity | No checksum | SHA256 required | Fact #6 |
| Weight hosting | Google Drive (mutable) | Needs pinned hash | Fact #6 |
| PyTorch version | Unspecified | ≥2.10.0 (CVE-2026-24747) | Fact #7 |

### 5. VRAM Budget

| Scenario | Draft04 | Proposed (XFeat VO) | Factual Basis |
|----------|---------|-------------------|---------------|
| VO models | SP 400 + LG 500 = 900MB | XFeat 200MB | Fact #15 |
| Satellite models | DINOv2 300 + LiteSAM 400 = 700MB | Same | Fact #15 |
| Peak total | ~1.6GB | ~900MB | Fact #15 |
| RTX 2060 headroom | 4.4GB free | 5.1GB free | Calculated |

### 6. GTSAM Robustness

| Aspect | Current | Needed | Factual Basis |
|--------|---------|--------|---------------|
| iSAM2 error handling | None specified | Catch IndeterminantLinearSystemException | Fact #13 |
| Long chain support | Assumed OK | Needs profiling, Bayes tree handles it | Fact #13 |
| Late anchor correction | Described | Works via Bayes tree structure | Fact #13 |

### 7. Satellite Imagery Freshness

| Aspect | Current Assumption | Reality | Factual Basis |
|--------|-------------------|---------|---------------|
| Google Maps Ukraine | "could be outdated for some regions" | 1-3 years old in conflict zones, intentionally | Fact #12 |
| Impact on matching | Not quantified | Significant degradation expected | Fact #12 |
| Alternatives | Mapbox as backup | Maxar (paid, 31-50cm), Tracasa (free, 2.5m) | Fact #16, #17 |
