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Video-Based Fire Detection

Thursday, February 26, 2009. Dynamic Textures can go Martin my distance! Thanks to Antoni Chan. Suffice it to say, I finished creating a function to compare two dynamic texture video sequences. The function finds the dynamic texture models of the two videos, it then then passes these two models to the Martin Distance function which in turn computes the distance between the two models based on the subspace angles between the models. Here's that confusion matrix where the diagonal has been set to infinity.

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Video-Based Fire Detection | firedetection.blogspot.com Reviews

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Thursday, February 26, 2009. Dynamic Textures can go Martin my distance! Thanks to Antoni Chan. Suffice it to say, I finished creating a function to compare two dynamic texture video sequences. The function finds the dynamic texture models of the two videos, it then then passes these two models to the Martin Distance function which in turn computes the distance between the two models based on the subspace angles between the models. Here's that confusion matrix where the diagonal has been set to infinity.

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5 motion color

6 frame differencing

7 status report

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9 feelings about opencv

10 actual progress

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Video-Based Fire Detection | firedetection.blogspot.com Reviews

https://firedetection.blogspot.com

Thursday, February 26, 2009. Dynamic Textures can go Martin my distance! Thanks to Antoni Chan. Suffice it to say, I finished creating a function to compare two dynamic texture video sequences. The function finds the dynamic texture models of the two videos, it then then passes these two models to the Martin Distance function which in turn computes the distance between the two models based on the subspace angles between the models. Here's that confusion matrix where the diagonal has been set to infinity.

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firedetection.blogspot.com

1

Video-Based Fire Detection: January 2009

http://firedetection.blogspot.com/2009_01_01_archive.html

Tuesday, January 27, 2009. Finally exterminated all of the bugs in the perceptron code. The following are the characteristics of the multilayer perceptron that I use for fire color detection:. 3 inputs, where each input is a color channel (e.g. R,G,B or H,S,V etc.). Trained for 100 epochs and got a mean squared error of 0.0033. More than 1 hidden node don't seem to help much and only end up slowing the classifier. Currently the classifier is trained on RGB color data. Posted by Nick True. Unfortunately w...

2

Video-Based Fire Detection: Devling into Dynamic Textures

http://firedetection.blogspot.com/2009/02/devling-into-dynamic-textures.html

Wednesday, February 18, 2009. Devling into Dynamic Textures. This past week I've shifted gears toward understanding and applying dynamic texture recognition to fire detection. I started by reading Dynamic Texture Recognition. By Saisan, P., Doretto, G., Wu, Y. N., and Soatto, S. which was a very confusing experience since it was missing all of the critical details. I then read the precursor paper Dynamic Textures. The next thing I did was to try to reproduce the algorithm laid out in Dynamic Textures.

3

Video-Based Fire Detection: No luck with Perceptrons...yet

http://firedetection.blogspot.com/2009/01/no-luck-with-perceptronsyet.html

Saturday, January 24, 2009. No luck with Perceptrons.yet. Well it turns out there were a few bugs/problems with my perceptron code. First off there was a problem reading in the input data which threw off the z-scaling. Then the z-scaling had some overflow problems which I fixed. Lastly, the initial weights were being set badly causing the perceptron to suck. I finally got it to work correctly on XOR. Posted by Nick True. Subscribe to: Post Comments (Atom). No luck with Perceptrons.yet.

4

Video-Based Fire Detection: I'm fired up!

http://firedetection.blogspot.com/2009/01/im-fired-up.html

Tuesday, January 27, 2009. Finally exterminated all of the bugs in the perceptron code. The following are the characteristics of the multilayer perceptron that I use for fire color detection:. 3 inputs, where each input is a color channel (e.g. R,G,B or H,S,V etc.). Trained for 100 epochs and got a mean squared error of 0.0033. More than 1 hidden node don't seem to help much and only end up slowing the classifier. Currently the classifier is trained on RGB color data. Posted by Nick True.

5

Video-Based Fire Detection: Dynamic Textures can go Martin my distance!

http://firedetection.blogspot.com/2009/02/dynamic-textures-can-go-martin-my.html

Thursday, February 26, 2009. Dynamic Textures can go Martin my distance! Thanks to Antoni Chan. Suffice it to say, I finished creating a function to compare two dynamic texture video sequences. The function finds the dynamic texture models of the two videos, it then then passes these two models to the Martin Distance function which in turn computes the distance between the two models based on the subspace angles between the models. Here's that confusion matrix where the diagonal has been set to infinity.

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Video-Based Fire Detection

Thursday, February 26, 2009. Dynamic Textures can go Martin my distance! Thanks to Antoni Chan. Suffice it to say, I finished creating a function to compare two dynamic texture video sequences. The function finds the dynamic texture models of the two videos, it then then passes these two models to the Martin Distance function which in turn computes the distance between the two models based on the subspace angles between the models. Here's that confusion matrix where the diagonal has been set to infinity.

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