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Advanced Face Recognition System for Casting Optimization
  1. case
  2. Advanced Face Recognition System for Casting Optimization

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Advanced Face Recognition System for Casting Optimization

moravio.com
Media
Entertainment
Film Production

Client's Challenge

Manual casting processes requiring extensive time and resources to identify suitable actors from large databases. Difficulty in efficiently finding visually similar performers to match character requirements, leading to increased production costs and scheduling delays.

About the Client

Established audiovisual production company seeking to modernize casting workflows through AI-driven solutions

Project Objectives

  • Develop a high-accuracy face recognition system for actor database searches
  • Implement real-time similarity matching to reduce casting decision time
  • Create cost-effective alternative to traditional casting workflows
  • Enable seamless integration with existing production management systems

System Requirements

  • Face detection and feature extraction from input images
  • Similarity scoring algorithm for actor comparisons
  • Real-time search functionality across distributed databases
  • AWS cloud infrastructure integration
  • DynamoDB data management for facial feature storage
  • Visual comparison interface with confidence metrics

Technology Stack

dlib
AWS
DynamoDB
Python
TensorFlow

System Integrations

  • Existing actor database APIs
  • Production scheduling software
  • Cloud storage solutions
  • User authentication systems

Performance Criteria

  • Scalability to handle 1M+ actor profiles
  • Response time under 2 seconds for similarity queries
  • 99.9% system availability
  • GDPR-compliant data handling
  • High accuracy in facial feature matching

Expected Business Impact

Projected 60-70% reduction in casting workflow duration, significant cost savings through automated candidate matching, improved casting accuracy through data-driven decisions, and enhanced operational scalability for large-scale productions.

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