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Cognitive Video Services

Accurate | Automated | Scalable

Cognitive Video Services

Cognitive Video Services

Accurate | Automated | Scalable

Trending

Trending

Unlocking new revenue streams using AI, Operators are shifting focus & also eyeing business opportunities in areas like Smart Home Services, Security & Surveillance Services, and Smart Infrastructure Service. Buying Trends survey shows a massive boost in AI and machine learning adoption in the broadcast and media industry, with 68% of organizations stating they are likely or very likely to deploy AI in the next 2-3 years. Applications for Digital Asset Management (DAM) are estimated to reach $8.1 billion by the end of 2024.

Trending
Opportunities & Challenges

Opportunities & Challenges

Opportunities & Challenges

Tagging and indexing large amounts of unstructured video data in real-time and efficiently is a major task, as it is usually performed manually. Unlike traditional rule-based automation processes, AI algorithms can analyse large amounts of data, mine patterns, compare data from multiple sources, and produce intelligent insights.

Efficient indexing and metadata tagging, on the other hand, necessitate sophisticated search techniques aimed at discovering media content snippets. Quality checks, subtitles, and closed caption formation have been traditionally performed manually. Anomaly identification and Natural Language Understanding (NLU) are two tools that AI can use to automate these tasks. Furthermore, AI can improve the consumer experience by examining consumption habits, social media footprint, demographic data of the local population, and dynamic insertion of highly specific ads, resulting in improved click-through rates.

Appropriate cost functions and hyper-parameter tuning help to fine-tune Deep Learning algorithms. A combination of algorithms such as CNN, RNN, LSTM, NLP, NLU, among others, should be optimized to achieve high accuracy and best performance for specific use cases.

Service Framework

Cognitive Video Services
Core Features

Image tagging

Hierarchical object detection

Named entity recognition such as Action detection, Scene recognition, Face recognition, Emotion Recognition, Strong Language

Explicit content & Violence detection

Automatic highlights generation for sports

Talk show Magic Moments creation

Service Features

Generic data repository

AI model repository for different applications

Speech & text-based query engine

Compatible across platforms

Cloud agnostic Application software

 

Differentiators

  • No dependency on training data collection
  • Generic data repository 
  • Customized inference packages   
  • Requirement specific expert systems   
  • Flexible architecture  
  • Ability to compute at the edge
  • A self-evaluating, continuous learning system
  • NLP/NLU/Context awareness

Benefits to the Customer

  • Reduce time-to-market by up to 50%
  • Algorithm accuracy of over 90% for face detection, eye-gaze, and head-pose detection already achieved
  • Easily customizable to suit customer needs
  • 50% Reduction in the time taken to generate Sports Match Highlights 
  • 80% Automation of Highlights & Violence Detection workflow is 80% more effective compared to the manual process

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