Software
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SSD-based plane tracking matlab toolbox.
In this toolbox we have implemented our Jacobian matrix factorisation for the projective motion model (see [Buenaposada02b] and [Hager98]). To test it out of the box, you should download the chessboard calibration template sequence (320x240 images) and decompress it over the same directory as the matlab toolbox (see the README.txt).
All publications and works that use this toolbox must reference our ICPR 2002 paper [Buenaposada02b]:
"Real-time tracking and estimation of plane pose", Jose M. Buenaposada, Luis Baumela. Proc. of International Conference on Pattern Recognition, ICPR 2002. Vol II, pp. 697-700, IEEE. Quebec, Canada, August 2002.
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Cohn-Kanade facial database apriori classification into the six universal expressions (anger, joy, disgust, fear, sadness, surprise) matlab scripts
The image sequences on the Cohn-Kanade facial database (at least on the public available part) are labeled with the FACS Action Units (AUs) present on the last image of each sequence. There is no direct translation from AUs into one of the universal expressions (most of the time the translation is subjetive). We believe that, in order to make fair comparations beetwen different classification results using the Cohn-Kanade database, it is needed to stablish some sort of benchmark (using the same training sequences and apriori classification).
We provide here two matlab scripts that sets which sequences we use and what apriori classification we made on the image sequences (from the Cohn-Kanade database).
All publications and works that use this image sequences must reference our PAA Journal paper:
"Recognising facial expressions in video sequences". J.M. Buenaposada, E. Muñoz, L. Baumela. Pattern Analysis and Applications Journal, 2008.
Image sequences
- Chess board calibration template sequence.
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Image sequences used in our BMVC 2006 paper.
All publications and works that use this image sequences must reference
our BMVC 2006 paper:
"Efficiently estimating facial expression and illumination in appearance-based tracking". J.M. Buenaposada, E. Muñoz, L. Baumela. 2006. British Machine Vision Conference, BMVC 2006. Edinburgh. September 2006.
![[ FIM UPM ]](images/fim.png)
![[ UPM ]](images/upm.png)