Sunday, October 30, 2011

3

CLEVERBOT: 59% HUMAN

Cleverbot is an Artificial Intelligence conversation system specially designed to learn from the conversations that it has with other people trying to mimic the human behavior in a conversation.



To find out the level of intelligence of this kind of artificial entities the archi-famous mathematician Alan Turing proposed in 1950 the Turing Test .  Basically, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All participants are separated from one another. If the judge cannot reliably tell the machine from the human, the machine is said to have passed the test.


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Every year the Turing Test  takes place, this year was celebrated on September 3rd at Techniche 2011, IIT Guwahati, India. In this scenario, several human judges had 5 minutes conversations with another entity (they ignored whether the entity was human or not). Some people believe that if 50% of the judges classify the entity they are talking to as human when in reality it is a machine, then the machine has passed the test. 

This year Cleverbot was classified as human 59% of the times and people might say it passed the Turing Test, but we humans still have hope... humans where classified as humans 63% of the time. I will start getting scared when Cleverbot is classified more often as a human than real humans xD

Anyway, it is fun to talk to Cleverbot, you really have to try it! How? You can do it right here! Just enter some text in the text bar above and hit the "Think About It!" button. Have fun!!

EDIT [2011/11/14]: I removed the widget to talk to Cleverbot directly because it was causing undesired behavior on the website. You can still talk to it by clicking on its logo and visiting Cleverbot's homepage.

Monday, October 10, 2011

7

STEREO VISION: 3D RECONSTRUCTION ERROR

Today I would like to publish the answer to another question in the comments of a previous post that might be worth its own post:

Hi Martin,

You gave such an informative article. Good Job Martin:-)

I'll explain steps that I performed in calculating distance of object.

1. Calibrated stereo camera with chessboard 8x6 cm with 2.8cm square size.

2. My calibration was success with rms error 0.206 and rectified images was good.

3. I found my interest point on left-right image. I tried to determine distance of object using method you specified. There is an error in distance measured from 3cm for closer object to 12cm or more for distant object.
Say, actual - 27cm ; measured - 24cm.
actual - 60cm ; measured - 48cm.


My queries are,
- why does there comes this much big varition is distance measurement?
- What may be reason/solution for this error?

Is there any mistake in my procedure or do i miss parameters?

Regards
Sathya Kumar

Dear Sathya,

First of all, thank you very much for your kind comment. Regarding your queries, I am afraid that what you describe is quite normal. The steps that you followed are correct, so I don't think that you did any mistake in your procedure or missed any parameters.

The thing is, that the relation between the disparity and the depth is non-linear.


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For this reason there is such a big variation in the distance measurement error, for close objects a small variation in disparity means a small variation on depth. But, for far objects a small variation in disparity means a big variation in depth.

So, there is no easy solution, it is unavoidable to get bigger error for distant objects, but you can try to mitigate the effects and reduce the error by getting a calibration as good as possible. And to do that you should take captures of the calibration pattern in as many different positions and orientations as possible, far, near, inclined, etc... Also increasing a bit the size of the chessboard could help you to get better accuracy for distant objects.

I hope this solved your doubts.

Best regards,
Martin

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