Character Aging Progression

Character Aging Progression

Create consistent character avatars from childhood through elderhood — maintaining identity while showing natural aging.

Staleness Watch: See EXTERNAL-API-REGISTRY.md for source URLs and recheck cadence

Summary

Workflow for generating age-progression image sets that maintain character identity across 13 life stages (ages 3-75). Uses nano-banana-pro with reference face image for facial consistency plus age-specific descriptors for natural aging.

Validated: Alex avatar set — 13 ages × successful generations

Life Stage Definitions

Implementation Pattern

Model Selection

Recommended: google/nano-banana-pro — Best face consistency with reference image Alternative: google/nano-banana-2 — Faster generation (Gemini 3.1 Flash), same API surface

const AGES = [3, 7, 13, 15, 18, 21, 25, 30, 42, 55, 62, 68, 75];

async function generateAgeProgression(characterConfig, referenceImage) {
  const results = [];
  
  for (const age of AGES) {
    const prompt = buildAgePrompt(characterConfig, age);
    const result = await replicate.run("google/nano-banana-pro", {
      input: {
        prompt,
        image_input: [await toDataURI(referenceImage)],  // Array of data URIs (up to 14)
        aspect_ratio: "1:1",
        output_format: "png"
      }
    });
    results.push({ age, url: result });
  }
  
  return results;
}

Critical: Use image_input (array) not image (single string). Pass at least one reference image; more references improve face consistency.

Age-Specific Prompt Templates

const AGE_DESCRIPTORS = {
  3: "3-year-old toddler, round chubby cheeks, large curious eyes, soft baby features, innocent expression",
  7: "7-year-old child, youthful face beginning to mature, bright curious eyes, playful yet thoughtful",
  13: "13-year-old teenager, face lengthening into adult proportions, youthful energy, intelligent gaze",
  15: "15-year-old teen, near-adult features emerging, fresh complexion, confident yet developing",
  18: "18-year-old young adult, adult features forming, youthful skin, mature confidence emerging",
  21: "21-year-old young professional, adult features fully formed, peak vitality, sharp intelligent eyes",
  25: "25-year-old adult, established features, confident bearing, professional demeanor",
  30: "30-year-old adult, subtle signs of maturity, experienced gaze, professional polish",
  42: "42-year-old, distinguished appearance, fine lines beginning, wisdom visible in eyes",
  55: "55-year-old, gray hair appearing at temples, crow's feet, dignified bearing, deep experience",
  62: "62-year-old senior, more pronounced lines, fuller silver hair, warm wise expression",
  68: "68-year-old, silver/white hair dominant, deep character lines, experienced wise gaze",
  75: "75-year-old elder, weathered dignified face, white hair, life experience visible, gentle wisdom"
};

function buildAgePrompt(character, age) {
  const baseDesc = character.coreIdentity;  // "Alex Finch, intelligent features, analytical eyes"
  const ageDesc = AGE_DESCRIPTORS[age];
  const style = character.style || "professional portrait, soft natural lighting, clean background";
  
  return `${baseDesc}, ${ageDesc}, ${style}`;
}

Critical Success Factors

1. Core Identity Markers (Constant)

Define 3-5 unchanging traits that persist across all ages:

• Eye color and shape
• Facial structure (bone structure)
• Distinctive features (e.g., dimples, nose shape)
• Expression tendencies

const CHARACTER = {
  coreIdentity: "Alex Finch, sharp intelligent features, " +
    "distinctive analytical eyes, determined jawline, " +
    "characteristic half-smile",
  // These traits appear in EVERY age prompt
};

2. Age-Appropriate Styling

Avoid anachronisms — match style to age:

• Children: Casual, age-appropriate clothing
• Teens: Contemporary teen fashion
• Adults: Professional attire
• Seniors: Dignified, comfortable styling

3. Reference Image Selection

Choose a reference that shows:

• Clear facial features at neutral angle
• Good lighting without harsh shadows
• Direct or 3/4 view (not profile)
• Age 18-30 works best as reference anchor

Cost Analysis

Best Practice: Generate ages 21 and 42 first to validate consistency before full set.

Quality Validation

Consistency Check

Compare across ages for:

1. Eye consistency — Same eye color/shape throughout
2. Feature evolution — Natural progression, not jarring changes
3. Identity preservation — Recognizably same person at all ages

Visual Verification (VS Code 1.112+)

Use view_image to review the full age progression set in sequence:

• Sequential scan — View images in age order to confirm smooth visual transitions
• Extremes comparison — Compare youngest (age 3) and oldest (age 75) for identity continuity
• Feature tracking — Verify eye color, facial structure, and distinctive features persist across all life stages
• Artifact detection — Flag any AI artifacts: impossible anatomy, smeared textures, broken age cues

Common Issues

File Organization

characters/
  {character-name}/
    reference/
      face-reference.png
    ages/
      Alex-03.png
      Alex-07.png
      ...
      Alex-75.png
    generation-report.json

Integration with Avatar System

Alex's avatar system uses age progression for:

1. Birthday fallback — Show user's age-matched Alex
2. Persona defaults — Age 21 is default when no persona detected
3. Age-appropriate identity — Users see Alex at their life stage

// From avatarMappings.ts
export const AVAILABLE_AGES = [3, 7, 13, 15, 18, 21, 25, 30, 42, 55, 62, 68, 75];

export function findClosestAge(age: number): number {
  // Returns nearest available age from set
}

Confidence Level

High — Empirically validated through:

• 13 age images generated for Alex character
• Consistent identity across full progression
• 768×768 optimized avatars deployed
• User birthday → age avatar mapping working