---
id: wiki-2026-0508-lighting-composition
title: "Lighting & Composition"
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [Cinematography, Visual Composition, Lighting Design]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [photography, cinematography, generative-AI, prompt-engineering]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: prompt
  framework: FLUX-Sora-Veo
---

# Lighting & Composition

## 매 한 줄
> **"매 image / video 의 emotional weight 의 90%는 lighting + composition"**. 매 subject 무엇이든, 매 light direction / quality, 매 frame organization 가 매 narrative 를 carry. 매 2026 의 generative AI (FLUX 1.1, Sora 2, Veo 3) 도 매 same vocabulary 를 prompt 로 받아 매 cinematographic control 가능.

## 매 핵심

### 매 lighting 의 axes
- **Direction**: front / side / back / top / bottom (각 emotional valence 다름).
- **Quality**: hard (sharp shadows) vs soft (diffused).
- **Color temperature**: warm (3000K) vs cool (6500K).
- **Ratio**: key:fill ratio (1:1 flat, 4:1 dramatic).

### 매 composition 의 axes
- **Rule of thirds**: 매 subject 매 third lines 의 intersection.
- **Leading lines**: 매 viewer's eye 의 directing.
- **Negative space**: 매 emptiness 가 carry meaning.
- **Depth layers**: foreground / mid / background.
- **Aspect ratio**: 16:9 (cinematic), 9:16 (mobile), 1:1 (square), 2.39:1 (anamorphic).

### 매 응용
1. **Photography**: portrait / product / landscape lighting setups.
2. **Cinematography**: 매 scene mood 의 establishing.
3. **Generative AI prompts**: 매 FLUX/Sora/Veo 매 cinematographic prompt vocabulary 인식.
4. **UI design**: 매 hero image direction selection.

## 💻 패턴

### Three-point lighting prompt
```
A portrait of a software engineer, three-point lighting: 
key light from camera-left at 45 degrees (soft, 5500K), 
fill light from camera-right at 1:2 ratio, 
backlight rim from upper-right (warm 3200K), 
shallow depth of field, 85mm lens equivalent, 
shot on Arri Alexa 35.
```

### Rembrandt lighting (FLUX 1.1 prompt)
```python
flux_prompt = """
Rembrandt lighting on subject's face: 
small triangle of light on shadow-side cheek, 
key light camera-left high at 45°, 
deep shadow on right side, 
chiaroscuro mood, oil painting aesthetic, 
photorealistic, 8K detail.
"""
```

### Golden hour video (Sora 2)
```python
sora_prompt = {
    "shot": "tracking shot through wheat field",
    "lighting": "golden hour, sun low at 15° angle camera-back-left, "
                "warm 2800K, long shadows, lens flare",
    "composition": "rule of thirds, horizon on lower third, "
                   "leading lines from wheat rows toward subject",
    "camera": "Steadicam, 24fps, 35mm anamorphic, T2.0",
    "duration_s": 8,
}
```

### Composition checker (CV-based QA)
```python
import cv2
import numpy as np

def rule_of_thirds_score(img: np.ndarray) -> float:
    """매 saliency map peak 매 third-line proximity."""
    h, w = img.shape[:2]
    saliency = cv2.saliency.StaticSaliencyFineGrained_create()
    _, sal = saliency.computeSaliency(img)
    peak_y, peak_x = np.unravel_index(sal.argmax(), sal.shape)
    third_lines_x = [w/3, 2*w/3]
    third_lines_y = [h/3, 2*h/3]
    dx = min(abs(peak_x - tx) for tx in third_lines_x) / w
    dy = min(abs(peak_y - ty) for ty in third_lines_y) / h
    return 1.0 - min(dx, dy) * 2  # higher = better composition
```

### Color temp grading (Veo 3 prompt augmentation)
```python
def grade_prompt(base: str, mood: str) -> str:
    grades = {
        "warm_nostalgic": "teal-orange grade, warm midtones (3200K), cool shadows",
        "cold_clinical": "desaturated blues, 6500K key, high-key flat lighting",
        "noir": "high-contrast B&W, low-key, single hard source, 4:1 ratio",
    }
    return f"{base} | grade: {grades[mood]}"
```

## 매 결정 기준
| Mood | Lighting | Composition |
|---|---|---|
| Heroic | Backlight rim + low-key fill | Low angle, centered |
| Intimate | Soft key, high ratio | Close-up, off-center |
| Tense | Hard side light, deep shadow | Dutch tilt, asymmetric |
| Whimsical | Bright fill, warm tones | Wide, symmetrical |
| Documentary | Available light | Eye-level, rule of thirds |

**기본값**: 매 three-point + rule of thirds — 매 safe baseline.

## 🔗 Graph
- 부모: [[Cinematography]]

## 🤖 LLM 활용
**언제**: 매 image/video prompt engineering — 매 cinematographic vocabulary 매 quality lift 큼.
**언제 X**: 매 abstract / non-representational generation — vocabulary 의 X.

## ❌ 안티패턴
- **Flat front lighting**: 매 amateur look — depth loss.
- **Centered everything**: 매 visual boring.
- **Mixed color temps unintentional**: 매 amateur giveaway.
- **Over-prompting**: 매 50+ tokens 의 lighting → 매 model confusion.

## 🧪 검증 / 중복
- Verified (Brown *Cinematography*; Block *Visual Story*; FLUX 1.1 prompt guide; Sora 2 system card 2025).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — lighting/composition vocabulary + 2026 generative AI prompts |