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Project Timeline (36-Hour Hackathon)

Hour 0-3: Ideation + Setup ✅

  • Project structure setup
  • Repository initialization
  • Team role assignment
  • Design wireframe
  • API research and selection

Deliverable: Organized project structure, clear roles


Hour 3-8: Frontend Scaffolding

  • A-Frame camera setup
  • Basic AR overlay system
  • UI controls (feature toggles)
  • Camera permission handling

Owner: Frontend Developer

Deliverable: Working camera feed with AR overlay framework


Hour 8-16: Speech-to-Text Captions

  • Web Speech API integration
  • Real-time caption display
  • AR text positioning
  • Timed fade-out animation

Owner: ML Developer + Frontend Developer

Deliverable: Live speech captions visible on camera feed


Hour 16-24: Sign Detection Prototype

  • MediaPipe Hands integration
  • TensorFlow.js model setup
  • Basic gesture classification (A-Z subset)
  • AR text overlay for signs

Owner: ML Developer

Deliverable: Recognizes a few ASL gestures and displays text


Hour 24-32: Scene + Object Description

  • TensorFlow.js COCO-SSD setup
  • Object detection implementation
  • Web Speech Synthesis integration
  • face-api.js emotion recognition

Owner: ML Developer + UX Lead

Deliverable: Audio narration of scenes and detected objects


Hour 32-40: Face Recognition + Firebase

  • face-api.js integration
  • Firebase Firestore setup
  • Face embedding storage/retrieval
  • AR memory tags for known faces
  • Add new face functionality

Owner: ML Developer + Backend Developer

Deliverable: Recognizes saved faces and displays personalized tags


Hour 40-44: Integration + Polish

  • Feature toggle UI
  • Error handling
  • Performance optimization
  • Accessibility improvements
  • Cross-browser testing

Owner: Entire Team

Deliverable: Polished, integrated application


Hour 44-48: Demo + Pitch Prep

  • Demo video recording
  • Presentation slides
  • Bug fixes
  • Final testing
  • Deployment

Owner: Entire Team

Deliverable: Working demo and presentation


Current Status

Current Phase: Setup Complete ✅

Next Steps: Frontend scaffolding