CVPR2010: Learnings from founding a computer vision startup: Chapter 0: Introduction
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CVPR2010: Learnings from founding a computer vision startup: Chapter 0: Introduction

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CVPR2010: Learnings from founding a computer vision startup: Chapter 0: Introduction Presentation Transcript

  • 1. Learnings from founding a computer vision startup Till Quack (kooaba) & Jan Erik Solem (Polar Rose)
  • 2. Learnings from founding a Computer Vision Startup Founded 2006, 10 employees Founders: Herbert Bay, Till Quack, Luc Van Gool Location: Zürich, Switzerland Object recognition for consumer applications On mobile and web Spin-off from ETH Zürich Still close relations to ETH
  • 3. kooaba makes images smarter Mobile Search (since 08/09)(more about products during talk) Auto-tagging (Q2 2010)
  • 4. Learnings from founding a Computer Vision Startup Till Quack PhD with Prof. Luc van Gool (graduated in 2009) Research interests: Object Recognition + Internet + Mobile kooaba founded during PhD Interests in innovation, product design etc. Two former companies (e.g. mosaickr.com with T. Weise and S. Saur. Sold in 2010.)
  • 5. Learnings from founding a Computer Vision Startup Founded 2004, 15 employees Malmö, Sweden: HQ, management, computer vision Warsaw, Poland: products, infrastructure Sophia-Antipolis, France: computer vision Spin-off from Lund University.
  • 6. Learnings from founding a Computer Vision Startup Face recognition for mobile, desktop and web
  • 7. Learnings from founding a Computer Vision Startup Jan Erik Solem PhD with Profs. Anders Heyden and Fredrik Kahl (graduated in 2006) Research interests: large-scale vision, object recognition and visual retrieval Polar Rose founded during PhD Interests in entrepreneurship, Web and mobile
  • 8. What to expect
  • 9. Learnings from founding a Computer Vision Startup What we learned along the way Flickr:kate at yr own risk
  • 10. Learnings from founding a Computer Vision Startup What’s special about Vision startups Flickr:Pete Prodoehl
  • 11. Learnings from founding a Computer Vision Startup Discussion between JES and TQ - and you Flickr: Katie Stine
  • 12. Learnings from founding a Computer Vision Startup Lots of pointers to resources Flickr:Ramkarthikblogger
  • 13. Learnings from founding a Computer Vision Startup Syllabus 1. Why a startup? JES / TQ 215-230 2. The business idea JES/TQ 230-245 3. Business plan: what and who to write it for? JES 245-300 4. Team JES 300-315 5. Funding: who and how to ask for money JES 315-330 Coffee Break 330pm-4pm 6. Product design: finding out what people really want TQ 400-430 7. Business models: how to make money? TQ 430-450 8. Software engineering: doing research vs. delivering a product TQ 450-520 9. Marketing & sales: getting people to know & buy your products TQ 520-545 10. Competition and positioning: OMG, Google is doing the same thing! JES 545-600
  • 14. Let’s start!