AI+ Video™

Módulos

• Module 1: Foundation of AI in Video Integration:
  1. 1.1 Basics of Video Processing
  2. 1.2 Introduction to AI in Video
  3. 1.3 Toolkits and Framework
  4. 1.4 Use Case: AI-enhanced Video Compression for Streaming Platforms
  5. 1.5 Case Study: YouTube’s AI-Driven Transcoding System
• Module 2: Preparing Video Data for AI:
  1. 2.1 Data Preparation for AI Models
  2. 2.2 Preprocessing and Augmenting Frames
  3. 2.3 Storage and Workflow Management
  4. 2.4 Use Case: Building AI-ready Video Datasets for Autonomous Driving Applications
  5. 2.5 Case Study: Tesla’s In-house Pipeline for Labeling Driving Scenarios across Multiple Geographies using Video Footage
  6. 2.6 Hands-On: Video Annotation using CVAT Tool, and Organizing them for Model Training
• Module 3: Machine Learning for Video Analysis:
  1. 3.1 Video Classification and Tagging
  2. 3.2 Object Detection and Movement Tracking
  3. 3.3 Action and Behavior Recognition
  4. 3.4 Use Case: Smart Surveillance Systems Detecting Abandoned Objects in Real Time
  5. 3.5 Case Study: Dubai Smart City’s AI Implementation for Object Recognition
  6. 3.6 Hands-On: Train YOLOv8 on Sample Security Footage to Detect and Track Objects
• Module 4: Generative AI in Video:
  1. 4.1 Generating Synthetic Video with GANs
  2. 4.2 AI-Driven Animation and Avatars
  3. 4.3 Ethical Use of Generative Content
  4. 4.4 Use Case: Auto-Generation of Product Explainer Videos using Avatars and Synthesized Narration
  5. 4.5 Case Study: Synthesia’s Solution Enabling Businesses to Create AI-Driven Training and Marketing Videos
  6. 4.6 Hands-On: Generate a Deepfake or AI Avatar using AKOOL, and Explore Face Alignment and Identity Swapping
• Module 5: Enhancing Video with AI:
  1. 5.1 Super-Resolution and Restoration
  2. 5.2 Real-Time Video Enhancement
  3. 5.3 Making Video More Inclusive
  4. 5.4 Use Case: Streaming Platforms using AI to Enhance Resolution and Reduce Latency for Mobile Users.
  5. 5.5 Case Study: DeOldify’s Impact in Reviving Historical Video Archives by Upscaling and Colorizing Black-and-White Footage.
  6. 5.6 Hands-On: Use AI4Video to Enhance a Sample Low-Resolution Black-and-White Video and Visualize Improvement
• Module 6: Interactive and Immersive AI Video:
  1. 6.1 AI in AR and Mixed Reality
  2. 6.2 Intelligent Video Editing
  3. 6.3 Viewer Engagement & Adaptation
  4. 6.4 Use Case: Live Sports Broadcasters using AR to Overlay Player Stats during Gameplay
  5. 6.5 Case Study: NFL and AWS Collaboration to Deliver Real-Time Performance Insights via Augmented Visuals.
  6. 6.6 Hands-On: Creating a Highlight Video from a Video Clip using Clipchamp
• Module 7: AI in Video Surveillance and Compliance:
  1. 7.1 Security and Monitoring Systems
  2. 7.2 Automated Content Moderation
  3. 7.3 Addressing Privacy and Ethics
  4. 7.4 Use Case: Automated Real-Time Access Control in Corporate Offices Using Facial Authentication.
  5. 7.5 Case Study: Amazon Go’s Cashier-less Stores Using Computer Vision for Security and Consumer Behavior Tracking
  6. 7.6 Hands-On: Implement Facial Detection and Access Control Simulation using OpenCV and a Basic Recognition Model
• Module 8: Future of AI+ Video:
  1. 8.1 Trends and Emerging Technologies
  2. 8.2 AI Applications by Industry
  3. 8.3 Careers and Professional Growth

Herramientas de IA

• TensorFlow
• PyTorch
• OpenCV
• MediaPipe
• Runway ML
• Synthesia Studio
• DeepFaceLab
• Adobe Sensei
• DaVinci Resolve Neural Engine
• Runway Gen-2
• Pika Labs
• Kaiber AI
• DeepBrain AI Studio
• NVIDIA Maxine SDK
• Google Video AI API
• FFmpeg Automation Tools
• Unreal Engine with AI Plugins
• Blender AI Add-ons
• Stability Video Diffusion
• Generative Video Editing Tools