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Image Recognition. Technology, Guidelines and Trends

Image Recognition has probably been one of the hottest topics throughout 2014 with announcements such as the launch of the Amazon FireFly app and several millions of VC capital and M&A in this space. Image recognition has the potential to become ubiquitous in our day-to-day interactions with real world objects that are connected with the digital world.

This talk will be divided in four topics. First, it will cover basic aspects of the technology: the different approaches, the type of objects that are recognized, and the limitations of each technique through demonstrations. Second, the audience will be guided through the steps required to embed an image recognition solution into an app or service. Third, a number of vendor solutions will be described to give hands on pointers for those willing to start integrating such solutions. Finally, the talk will discuss the future of image recognition in different fields.

You can watch the video of the presentation here: https://www.youtube.com/watch?v=ilbTvfchtQY

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Image Recognition. Technology, Guidelines and Trends

  1. 1. Image Recognition Technology, Guidelines and Trends David Marimon CEO & Co-founder david@catchoom.com +34 654 906 753
  2. 2. The visual recognition market is estimated to grow from $9.65 billion in 2014 to $25.65 billion by 2019 According to Image Recognition Market, Markets and Markets, May 2014
  3. 3. Image Recognition Face Recognition Object Classification Object Character Recognition Visual Recognition
  4. 4. Augmented Reality and Image Recognition, the happy couple
  5. 5. Outline What works with image recognition How to put image recognition into your app Vendor comparison Trends
  6. 6. Outline What works with image recognition How to put image recognition into your app Vendor comparison Trends
  7. 7. How does the world look like for a machine? Textured Textureless Transparent Deformable Rigid
  8. 8. What’s possible with Image Recognition? Textured Textureless Transparent Deformable Rigid
  9. 9. Outline What objects work with image recognition How to put image recognition into your app Vendor comparison Trends
  10. 10. What do you need to build an app? Content On-device or Cloud Image Recognition Image database
  11. 11. Curate the Image Database
  12. 12. Choose the IR mode that fits best Cloud Service On-Device SDK
  13. 13. Choose the IR mode that fits best Cloud Service On-Device SDK IR requires Internet Yes No IR speed Depends on network Controlled Content updates Immediate Require local sync Analytics Latest available Rely on app connection
  14. 14. Outline What works with image recognition How to put image recognition into your app Vendor comparison Trends
  15. 15. Cloud Service On-Device SDK Vendors in the AR space
  16. 16. Service On Premises On-Device Vendors in the IR space
  17. 17. Why my favorite is Catchoom Real World- tested Built for usability Fast, accurate, reliable Scalable
  18. 18. Catchoom has delivered over 420 million image recognitions to date
  19. 19. Outline Image recognition: approaches and limitations How to put image recognition into your app Vendor comparison Trends
  20. 20. Extended Search On-Device SDK Cloud Service
  21. 21. Industrial Applications
  22. 22. Apparel recognition
  23. 23. Takeaways 1. Image recognition is the door to a broad range of applications and services 2. Improve performance with better image databases 3. Choose on-device or cloud IR depending on your use case. 4. Catchoom is already behind 420M interactions and looking to meet upcoming trends
  24. 24. Image Recognition Technology, Guidelines and Trends David Marimon CEO & Co-founder david@catchoom.com +34 654 906 753 Visit our booth for live demos!
  25. 25. Annex
  26. 26. Image Recognition vs Object Classification Textured Textureless Transparent Deformable Rigid Image Recognition Object Classification
  27. 27. Challenges with benchmarks Label a database with both reference and test images Identify infrastructure differences Understand performance is not necessarily optimized for your use case
  28. 28. How to benchmark Small dataset Full test 1. Contact the vendor 1. Contact the vendor 2. Label your database 3. Use APIs

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