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Sebastien PARIS

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Company/University
LSIS/DYNI, Aix-Marseille University (AMU), UMR CNRS 7296

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Professional Interests:
Statistics, Optimization, Machine Learning, Signal Processing, Target Tracking

 

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Files Posted by Sebastien View all
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24 Mar 2012 Screenshot Fast K-means clustering Fast mex K-means clustering algorithm with possibility of K-mean++ initialization. Author: Sebastien PARIS statistics, image processing, mathematics 90 0
15 Mar 2012 Screenshot Free Split and Merge Expectation Maximization for MultiVariate Gaussian Mixture FSMEM can estimate MVGM parameters and number of conpounds via split/merge cluster moves Author: Sebastien PARIS split and merge, clustering, signal processing, optimization, em, mathematics 45 14
19 Jan 2012 Screenshot EM for HMM Multivariate Gaussian processes A fast implementation of the EM Algorithm for HMM Multivariate Gaussian Mixture Author: Sebastien PARIS probability, multivariate gaussian..., hmm, em, statistics, forwardbackward 47 10
  • 5.0
5.0 | 3 ratings
19 Jan 2012 Screenshot EM_MVGM Fast implementation of EM algorithm for multivariate gaussian mixture Author: Sebastien PARIS statistics, probability, expectationmaximizati..., multivariate gaussian... 23 7
19 Jan 2012 Screenshot NDellipse Returns coordinates of 2d ellipsoids Author: Sebastien PARIS statistics, probability, 2dellipsoidnd slices 6 0
  • 5.0
5.0 | 1 rating
Comments and Ratings by Sebastien View all
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17 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS

Lucas,

You are right, I will change the description in Haar_featlist and dependencies

  ny Number of rows of the pattern (default ny = 24)
  nx Number of columns of the pattern (default nx = ny)
  rect_param Features rectangles parameters (10 x nR), where nR is the total number of rectangles for the patterns.
                    (default Vertical(2 x 1) [1 ; -1] and Horizontal(1 x 2) [-1 , 1] patterns)
rect_param(: , i) = [ip ; wp ; hp ; nrip ; nr ; xr ; yr ; wr ; hr ; sr], where
if index of the current Haar's feature. ip = [1,...,nF], where nF is the total number of Haar's features
wp width of the current rectangle pattern defining current Haar's feature
hp height of the current rectangle pattern defining current Haar's feature
nrif total number of rectangles for the current Haar's feature if
nr index of the current rectangle in the current Haar's feature, nr=[1,...,nrif]
xr,yr top-left coordinates of the current rectangle of the current pattern
wr,hr width and height of the current rectangle of the current pattern
sr weights of the current rectangle of the current pattern

Please run gui_features_dictionary in the \gui subdir to build such parameters

  Outputs
  -------
  
  F Features's list (6 x nF) in UINT32 where nF designs the total number of Haar features
                    F(: , i) = [if ; xf ; yf ; wf ; hf ; ir]
if index of the current feature, if = [1,....,nF] where nF is the total number of Haar's features (see nbfeat_haar function)
xf,yf top-left coordinates of the current Haar's feature
wf,hf width and height of the current feature Haar's feature
ir Linear index of the FIRST rectangle of the current Haar's feature according rect_param definition. ir is used internally in Haar function
(ir/10 + 1) is the matlab index of this first rectangle

13 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS

Tsai,

Let me clarify :
ir Linear index of the FIRST rectangle of the current Haar feature according rect_param definition. ir is used internally in Haar function. (ir/10 + 1) is the matlab index of this first rectangle

Hope will help you ...
13 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS

Tsai,

If compilation with -DOMP was succesfull, now you can add a num_threads = number of core in the options structure. Please open *.c header for full instructions.
21 Mar 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS

levgenia,

Yes you have to fill the positives folder. Please read the readme.txt to find datasets of positives samples for face detection.
15 Mar 2012 Particle Filter Color Tracker Tracking an object in a video with a Color Particle Filter Author: Sebastien PARIS

Ching-Chun: 2009b win64 ?
Can you put a break point to stop at errors ?
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30 Apr 2012 Scenes/Objects classification toolbox Scenes recognition toolbox for vision systems Author: Sebastien PARIS Weixia

Dear Sebastian,
Thank you for sharing this remarkable toolbox!
I've just installed the toolbox and run the bag_of_features.m, but unfortunately, en error was reported. It said that "Undefined function 'dltrain' for input argument of type 'struct'."
Error in extract_bag_of_features (line 229)
                    D(: , : , s , c) = encoding(X(: , indexdico) ,
                    encoding_param{current_encoding}{current_descriptor});

Could you please so kind to help me with this little problem? I am really an new hand in this area...
Best wishes!
Weixia
30 Apr 2012 Scenes/Objects classification toolbox Scenes recognition toolbox for vision systems Author: Sebastien PARIS Weixia
17 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS PARIS, Sebastien

Lucas,

You are right, I will change the description in Haar_featlist and dependencies

  ny Number of rows of the pattern (default ny = 24)
  nx Number of columns of the pattern (default nx = ny)
  rect_param Features rectangles parameters (10 x nR), where nR is the total number of rectangles for the patterns.
                    (default Vertical(2 x 1) [1 ; -1] and Horizontal(1 x 2) [-1 , 1] patterns)
rect_param(: , i) = [ip ; wp ; hp ; nrip ; nr ; xr ; yr ; wr ; hr ; sr], where
if index of the current Haar's feature. ip = [1,...,nF], where nF is the total number of Haar's features
wp width of the current rectangle pattern defining current Haar's feature
hp height of the current rectangle pattern defining current Haar's feature
nrif total number of rectangles for the current Haar's feature if
nr index of the current rectangle in the current Haar's feature, nr=[1,...,nrif]
xr,yr top-left coordinates of the current rectangle of the current pattern
wr,hr width and height of the current rectangle of the current pattern
sr weights of the current rectangle of the current pattern

Please run gui_features_dictionary in the \gui subdir to build such parameters

  Outputs
  -------
  
  F Features's list (6 x nF) in UINT32 where nF designs the total number of Haar features
                    F(: , i) = [if ; xf ; yf ; wf ; hf ; ir]
if index of the current feature, if = [1,....,nF] where nF is the total number of Haar's features (see nbfeat_haar function)
xf,yf top-left coordinates of the current Haar's feature
wf,hf width and height of the current feature Haar's feature
ir Linear index of the FIRST rectangle of the current Haar's feature according rect_param definition. ir is used internally in Haar function
(ir/10 + 1) is the matlab index of this first rectangle

13 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS Chai, Lucas

Am I clear? I mean in function F = haar_featlist([ny] , [nx] , [rect_param]), the first parameter of the output F in ur description is iF(1,..,nF), but the result value shows it is actually the ip (index of the pattern in options.rect_param), u can check it.

And for the last parameter ir, if (ir/10+1)is given, the meaning is obvious, thanx again
13 Apr 2012 Objects/Faces Detection Toolbox Objects/Faces detection using Local Binary Patterns and Haar features Author: Sebastien PARIS PARIS, Sebastien

Tsai,

Let me clarify :
ir Linear index of the FIRST rectangle of the current Haar feature according rect_param definition. ir is used internally in Haar function. (ir/10 + 1) is the matlab index of this first rectangle

Hope will help you ...
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statistics, probability, optimization, mathematics, multivariate gaussian mixture
Files Tagged by Sebastien View all
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Updated   File Tags Downloads
(last 30 days) 		Comments Rating
24 Mar 2012 Screenshot Fast K-means clustering Fast mex K-means clustering algorithm with possibility of K-mean++ initialization. Author: Sebastien PARIS statistics, image processing, mathematics 90 0
15 Mar 2012 Screenshot Free Split and Merge Expectation Maximization for MultiVariate Gaussian Mixture FSMEM can estimate MVGM parameters and number of conpounds via split/merge cluster moves Author: Sebastien PARIS split and merge, clustering, signal processing, optimization, em, mathematics 45 14
19 Jan 2012 Screenshot EM for HMM Multivariate Gaussian processes A fast implementation of the EM Algorithm for HMM Multivariate Gaussian Mixture Author: Sebastien PARIS probability, multivariate gaussian..., hmm, em, statistics, forwardbackward 47 10
  • 5.0
5.0 | 3 ratings
19 Jan 2012 Screenshot EM_MVGM Fast implementation of EM algorithm for multivariate gaussian mixture Author: Sebastien PARIS statistics, probability, expectationmaximizati..., multivariate gaussian... 23 7
19 Jan 2012 Screenshot NDellipse Returns coordinates of 2d ellipsoids Author: Sebastien PARIS statistics, probability, 2dellipsoidnd slices 6 0
  • 5.0
5.0 | 1 rating

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