wedding-immortalist

Use for:

• Processing thousands of wedding photos into 3DGS scenes
• Creating theatre-mode experiences where ceremony/reception moments play in-place
• Building face-clustered guest rosters with best-photo selection
• Matching design aesthetics to wedding themes (disco, rustic, beach, modern, queer celebrations)
• AI-curated photo selection per guest with aesthetic scoring

NOT for:

• General photo editing → use native-app-designer
• Non-wedding 3DGS → use drone-inspection-specialist
• Event planning → not a wedding planner
• Video editing without 3D reconstruction

```

┌─────────────────────────────────────────────────────────────────┐

│ WEDDING IMMORTALIST PIPELINE │

├─────────────────────────────────────────────────────────────────┤

│ │

│ 1. INGEST 2. RECONSTRUCT 3. CLUSTER │

│ ├─ Photos (1000s) ├─ COLMAP SfM ├─ Face detect │

│ ├─ Video (hours) ├─ 3DGS training ├─ Embeddings │

│ └─ Audio/speeches └─ Scene merge └─ Identity link │

│ │

│ 4. CURATE 5. DESIGN 6. PRESENT │

│ ├─ Aesthetic score ├─ Theme extract ├─ Web viewer │

│ ├─ Per-person best ├─ Color palette ├─ Theatre mode │

│ └─ Moment detect └─ Typography └─ Guest roster │

│ │

└─────────────────────────────────────────────────────────────────┘

```

Theme Detection & Matching

Every wedding has a unique aesthetic. Extract and honor it:

| Theme Type | Color Palette | Typography | UI Elements |

|------------|---------------|------------|-------------|

| 70s Disco | Gold, orange, burnt sienna, deep purple | Groovy script, bold sans | Mirror balls, starbursts, warm gradients |

| Rustic/Barn | Earth tones, sage, cream, wood | Serif, hand-lettered | Burlap textures, wildflower accents |

| Beach/Coastal | Ocean blues, sand, coral, seafoam | Light sans, script | Shell motifs, wave patterns |

| Modern Minimal | Black, white, metallics | Clean geometric sans | Sharp lines, negative space |

| Queer Joy | Rainbow spectrums, bold colors | Expressive, varied | Pride elements, celebration maximalism |

| Cultural Fusion | Per tradition | Traditional + modern | Cultural motifs, heritage patterns |

Extracting Theme from Photos

```python

# Theme extraction signals

THEME_SIGNALS = {

'color_palette': 'Dominant colors from venue, florals, attire',

'lighting_mood': 'Warm/cool, natural/dramatic, string lights/chandeliers',

'decor_elements': 'Rustic/modern/vintage/eclectic',

'attire_style': 'Traditional/non-traditional, formal/casual',

'cultural_markers': 'Religious symbols, cultural traditions',

'era_aesthetic': '70s disco, 20s gatsby, etc.'

}

```

Photo/Video Ingestion

```

Optimal Input Strategy:

├── Video: Extract 2-3 fps (80% overlap minimum)

├── Photos: Include ALL photographer shots

├── Phone photos: Guest uploads (georeferenced bonus)

└── Coverage: Ceremony + reception + all spaces

Quality Thresholds:

├── Minimum images per space: 50-100

├── Overlap requirement: 60-80%

├── Blur rejection: Laplacian variance < 100 = skip

└── Exposure: Reject severe over/underexposure

```

COLMAP Structure from Motion

```bash

# Feature extraction

colmap feature_extractor \

--database_path database.db \

--image_path images/ \

--ImageReader.single_camera 0 \

--SiftExtraction.max_image_size 3200

# Exhaustive matching for comprehensive coverage

colmap exhaustive_matcher \

--database_path database.db \

--SiftMatching.guided_matching 1

# Sparse reconstruction

colmap mapper \

--database_path database.db \

--image_path images/ \

--output_path sparse/

# Dense reconstruction (optional, for mesh)

colmap image_undistorter ...

colmap patch_match_stereo ...

```

3DGS Training

```python

# Wedding-optimized 3DGS settings

WEDDING_3DGS_CONFIG = {

'iterations': 50_000, # High quality for permanent archive

'densify_from_iter': 500,

'densify_until_iter': 15_000,

'densification_interval': 100,

'opacity_reset_interval': 3000,

'sh_degree': 3, # Full spherical harmonics for lighting

'percent_dense': 0.01,

'densify_grad_threshold': 0.0002,

}

# Multi-space merge strategy

SPACES = ['ceremony', 'cocktail_hour', 'reception', 'photo_booth', 'dance_floor']

# Train each separately, then create unified navigation

```

Pipeline

```

┌────────────────────────────────────────────────────────┐

│ FACE CLUSTERING PIPELINE │

├────────────────────────────────────────────────────────┤

│ 1. Detection (RetinaFace/MTCNN) │

│ └─ All faces in all photos │

│ 2. Alignment (5-point landmark) │

│ └─ Standardize for embedding │

│ 3. Embedding (ArcFace/AdaFace) │

│ └─ 512-dim identity vector per face │

│ 4. Clustering (HDBSCAN) │

│ └─ Group by identity, handle edge cases │

│ 5. Identity Linking │

│ └─ Match to couple, wedding party, family, guests │

│ 6. Best Photo Selection │

│ └─ Aesthetic scoring per cluster │

└────────────────────────────────────────────────────────┘

```

Clustering Parameters

```python

CLUSTERING_CONFIG = {

'min_cluster_size': 3, # At least 3 photos to form identity

'min_samples': 2,

'metric': 'cosine',

'cluster_selection_epsilon': 0.3,

'cluster_selection_method': 'eom',

}

# Identity priority for naming

IDENTITY_PRIORITY = [

'couple_1', 'couple_2', # The married couple

'wedding_party', # Bridesmaids, groomspeople

'parents', # Parents of the couple

'grandparents',

'siblings',

'extended_family',

'friends',

'vendors', # Photographer, DJ, etc.

]

```

Identity Linking Workflow

1. Couple identification: User tags couple in 2-3 photos
2. Wedding party: User identifies key people
3. Auto-propagation: Embeddings match across all photos
4. Guest matching: Optional guest list import for name assignment
5. Manual corrections: UI for fixing mismatches

Per-Photo Quality Metrics

```python

AESTHETIC_FEATURES = {

# Technical quality

'sharpness': 'Laplacian variance, MTF analysis',

'exposure': 'Histogram analysis, dynamic range',

'noise': 'High-ISO detection, grain analysis',

# Composition

'rule_of_thirds': 'Subject placement scoring',

'symmetry': 'For venue/group shots',

'framing': 'Negative space, balance',

# Face-specific

'expression': 'Smile detection, eye openness',

'blink_detection': 'Eyes closed penalty',

'gaze_direction': 'Looking at camera vs. candid',

'face_occlusion': 'Nothing blocking the face',

'face_lighting': 'Even illumination, no harsh shadows',

# Emotional

'genuine_smile': 'Duchenne marker detection',

'moment_quality': 'Laughter, tears, embraces',

}

```

Best Photo Selection Per Person

```python

def select_best_photos(cluster_photos, n=5):

"""Select top N photos for a person across all their appearances."""

scores = []

for photo in cluster_photos:

score = (

0.25 * technical_quality(photo) +

0.25 * composition_score(photo) +

0.30 * expression_quality(photo) +

0.20 * context_diversity(photo, scores) # Avoid all similar shots

)

scores.append((photo, score))

# Select top N with diversity constraint

return diverse_top_n(scores, n, diversity_threshold=0.7)

```

Moment Detection & Playback

```

KEY MOMENTS (auto-detected + user-tagged):

├── Ceremony

│ ├── Processional

│ ├── Vows exchange

│ ├── Ring ceremony

│ ├── First kiss

│ └── Recessional

├── Reception

│ ├── Grand entrance

│ ├── First dance

│ ├── Parent dances

│ ├── Toasts/speeches

│ ├── Cake cutting

│ └── Bouquet/garter

├── Party

│ ├── Dance floor highlights

│ └── Exit/sendoff

└── Candids

├── Emotional moments (tears, laughter)

└── Spontaneous joy

```

In-Scene Video Projection

```

Theatre Mode Rendering:

1. User navigates 3DGS scene freely
2. Approaches "moment marker" (glowing orb/frame)
3. Video/slideshow plays IN the 3D space

├── On walls where projector was

├── Floating frames in dance floor area

└── Photo booth backdrop location

1. Spatial audio for speeches/music
2. User can pause, scrub, exit to continue exploring

```

```javascript

// Wedding Immortalist Viewer Components

const VIEWER_FEATURES = {

// 3DGS Navigation

gaussianSplatting: {

renderer: 'three-gaussian-splat',

navigation: 'orbit + first-person',

qualityLevels: ['preview', 'standard', 'maximum'],

},

// Theatre Mode

theatreMode: {

momentMarkers: true,

videoInScene: true,

spatialAudio: true,

transitionEffects: 'theme-matched',

},

// Guest Roster

guestRoster: {

faceGrid: 'clustered by identity',

photoGallery: 'per-person best shots',

searchByName: true,

shareableLinks: 'per-guest galleries',

},

// Theme

theming: {

colorPalette: 'extracted from wedding',

typography: 'theme-matched',

uiElements: 'aesthetic-consistent',

},

};

```

"All Frames, All the Time"

Wrong: Extracting every video frame for 3DGS.

Why: Redundant data, 10x slower processing, no quality improvement.

Right: 2-3 fps extraction with motion-based keyframe selection.

"One Giant Scene"

Wrong: Training single 3DGS for entire venue.

Why: Memory explosion, quality degradation, impossible on consumer hardware.

Right: Train per-space, create unified navigation with seamless transitions.

"Default Clustering Threshold"

Wrong: Using default HDBSCAN settings.

Why: Wedding photos have varying lighting, makeup, angles—need tuning.

Right: Tune per-wedding based on photo count and quality variance.

"Ignoring Theme"

Wrong: Generic white/gray viewer UI for disco wedding.

Why: Destroys the personality and joy of the event.

Right: Extract and honor the couple's aesthetic choices.

"Photographer Only"

Wrong: Using only professional photos.

Why: Misses candid moments, guest perspectives, coverage gaps.

Right: Merge professional + guest photos for complete coverage.

Shareable Guest Galleries

```

Per-Guest Experience:

├── Personalized link: yourwedding.com/guests/aunt-martha

├── Their best photos (AI-curated)

├── Photos with the couple

├── Group photos they appear in

├── Download options (full-res)

└── "Add to my memories" for their own archives

```

Collaborative Enhancement

```

Guest Contribution Portal:

├── Upload their own photos

├── Tag themselves in unidentified clusters

├── Correct misidentifications

├── Add names to unknown guests

└── Submit video moments they captured

```

```

wedding-immortalist-output/

├── 3dgs-scenes/

│ ├── ceremony/

│ ├── cocktail/

│ ├── reception/

│ └── unified-navigation.json

├── guest-roster/

│ ├── face-clusters/

│ ├── identity-mapping.json

│ └── per-person-galleries/

├── theatre-mode/

│ ├── moment-markers.json

│ ├── video-segments/

│ └── spatial-audio/

├── web-viewer/

│ ├── index.html

│ ├── theme-config.json

│ └── assets/

└── exports/

├── full-resolution-photos/

├── guest-gallery-zips/

└── video-compilations/

```

• drone-inspection-specialist: 3DGS techniques, COLMAP pipeline
• collage-layout-expert: Photo arrangement, aesthetic composition
• color-theory-palette-harmony-expert: Theme color extraction
• clip-aware-embeddings: Photo-text matching for search
• photo-composition-critic: Aesthetic quality scoring

---

Core Philosophy: A wedding happens once. The memories should live forever. This skill transforms ephemeral moments into an eternal, explorable experience that honors the couple's unique celebration—whether it's a disco dance party, a rustic barn gathering, or two grooms celebrating their love with chosen family.