21–30 of 74 posts
Tried detecting Airplanes on this image with 18 airplanes, but it only detected 4 of them. https://lh3.ggpht.com/-GbPgbhUtmnE/UH0p3VmMWoI/AAAAAAAAApM/u...
As a long time CV enthusiast, I applaude the tech and the way you guys make it "just work". However for any serious application I feel a few things are missing: - your pricing won't work for video (even at only 5fps) - I can't really use the data without a confidence level of detection. Because for some applications I'd rather discard a bouding box that is below a threshold I set. Other than that, congrats for the gr…
In the meantime, if you want to experiment with Dextro for video, shoot us an email at team@dextrorobotics.com and we will hook you up!
With regard to confidence level, that's something that we provide the enterprise-class service with; if this is a critical feature, we can potentially offer it to everyone as well.
Failed completely for me across a half dozen tries. I wonder how cheaply you could get results via Mechanical Turk. I bet you could get much more accurate results for a very low price but with some added latency.
Language dependent/creative tasks run much higher (smaller worker pool, more brain power needed).
One thing that I want to mention: our service was built favoring Precision over Recall; we reasoned that we'd rather have a low number of false positives and make sure that when we do report a detection, that it actually is one. Thus, our service may occasionally miss instances.
I'm going to implement a button on the Experiment page that lets you flag a detection as something that we need to work on; we will use your feedback to improve the accuracy.
Tried detecting Airplanes on this image with 18 airplanes, but it only detected 4 of them. https://lh3.ggpht.com/-GbPgbhUtmnE/UH0p3VmMWoI/AAAAAAAAApM/u...
The browser demo page says "Dextro supports up to 4 objects to be detected concurrently when used via the full API.", I think that's the problem.
I want to clarify: the 4 object concurrent detection refers to 4 classes of objects. On the Experiment page, you can only choose one class to detect on (whether that is person, bottles, cars, etc). However, by using the API, you can simultaneously search for cars, planes, people, and motorcycles, for example.
Did a few tests and it works pretty well! No false positives at least. Any plans to increase the number of objects you can search for at once? Very interested in using this but I'd want to be able to scan for ~20 objects.
http://artificial-intelligence-projects.com/augmented-realit...
It's still in the development stage because I can only fiddle with it when I have the time and impetus to do so. Criticisms/comments welcome.
The idea was a simple (but clever) one - use virtual reality to segment the world into solid blocks of identified objects. The solid blocks are identifiable to those with poor vision in a way that the real world is not.
Essentially this meant processing an image, identifying items e.g. cars, fences, roads etc and then colouring them solid. So instead of a confusing scene of blur, you have a blurred but still identifiable scene of a solid strip of grey for the road, a solid blob of red for the car, another solid yellow stip for a fence etc. A poorly sighted person could still identify from this something that made sense in a way that they couldn't in the real world.
What was required was an input, real time visual processing and then display back to the user - all of which was fantasy 15 year ago.
However, attempt this today with a visual feed, real time processing like this, and then near instantaneous display of the results back to the person with e.g. google glass, and you might have a viable way to show the world categorised in a visual way that will help those with poor vision. Interesting times.
Failed completely for me across a half dozen tries. I wonder how cheaply you could get results via Mechanical Turk. I bet you could get much more accurate results for a very low price but with some added latency.
One to two cents a task. Anytime you have a language agnostic task (identifying/classifying objects, etc), the tasks can be done very cheaply. Just make sure you do triplicate validation. Language dependent/creative tasks run much higher (smaller worker pool, more brain power needed).
http://3rdarm.biz/images/2010/02/faces.jpg
It got almost all of them but so many errors. It can't detect sheeps either.
I was really impressed at first, but as I tried out more and more images, it became apparent that the api isn't mature enough for one or two cents worth of money. There is a 90% of the algorithm detect the image correctly, but sometimes it doesn't detect the entire object. For example, I used another image of two jets, but it only found one of them even though the jets were identical, but one was smaller than the other.
