3. Learnings from founding a Computer Vision Startup
Basic competition check (again)
www.crunchbase.com
4. Differentiation
Learnings from founding a Computer Vision Startup
How are you different from your competition?
(performance, features, geographic, price, business model, ...)
5. Learnings from founding a Computer Vision Startup
How to handle competition?
Be aware of who competitors are and what they do (you need to be
able to answer when people ask)
But...
Focus on your own ideas and on making your product great
Be inspired if competition does something good but don’t copy or
follow blindly - copying lacks understanding, better think for yourself
Competitors might have a different agenda and goals
And...
Don’t worry - a reasonable amount of competition is good for all
6. Learnings from founding a Computer Vision Startup
OMG, what happens if Google is doing “the same”?
- they never really do the exact same thing
- they most likely have a different goal
- they most certainly have a different business model
- they have competitors who might want partners (you)
7. Learnings from founding a Computer Vision Startup
Polar Rose: How we did it
Case 1: Picasa & iPhoto
Google Picasa added face recognition for people tagging in fall 2008
Apple’s iPhoto added the same in January 2009
At the same time we were doing people tagging at polarrose.com (Flickr/Facebook)
End result: Picasa and iPhoto drive competitors to feature parity
8. Learnings from founding a Computer Vision Startup
Polar Rose: How we did it
Case 2: Goggles
Google Goggles launched late fall 2009
with supposed face recognition feature disabled
At the same time we had the Augmented ID / Recognizr app
End result: still unclear, but large players are more careful,
small startups can take risks and provoke. Again a drive for
feature parity elsewhere is emerging.
9. Learnings from founding a Computer Vision Startup
“Traction”
first iPhone
MMS campaign
with easyjet
first version visual search
iPhone SDK
Worlds first iPhone app
$$ Seed
for visual search
> 1 million items in DB
Amazon acquires snaptell
kooaba Tech Talk
@ Google(USA)
$$ Angel
> 10 million items in DB
Q2/07 Q3/07 Q4/07 Q1/08 Q2/08 Q3/08 Q4/08 Q1/09 Q2/09 Q3/09 Q4/09 Q1/10
A brief history of visual search and kooaba
12. Learnings from founding a Computer Vision Startup
Things we didn’t cover
Some boring parts:
IP & patents
How to handle admin stuff (bank, bookkeeping, legal,...)
Office & finding a good place to work
B2B licensing alternatives and structures
How to do consultancy work
Deeper into certain topics we presented today.
We could tell you next CVPR if you want ;)
13. Learnings from founding a Computer Vision Startup
Take home messages
Starting out is cheaper and easier than you think
Focus on core functionality and engage customers early
Vision is about to enter consumer market, timing is good
Lots of the things we learned and told you today turn out to be
“just” (advanced) common sense.
14. Learnings from founding a Computer Vision Startup
Vision specific lessons
Vision is magic to many, explanations often needed
Complex technology (you will need funding / quality in product
development)
Business models in B2C often unclear (innovation is needed here, too)
But huge opportunities for you as an expert, if you’re not a total techie ;)
16. The End
Till Quack Jan Erik Solem
quack@kooaba.com www.polarrose.com
www.kooaba.com janerik@polarrose.com
@tmdq @jesolem
www.quack.ch www.janeriksolem.net
Slides will be online!
http://www.vision.ee.ethz.ch/tquack/cvpr10-tutorial.html
