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diff --git a/debian/man/opencv_createsamples.1 b/debian/man/opencv_createsamples.1
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+.TH "OPENCV_CREATESAMPLES" "1" "May 2010" "OpenCV" "User Commands"
+
+
+.SH NAME
+opencv_createsamples \- create training and testing samples
+
+
+.SH SYNOPSIS
+.B opencv_createsamples [options]
+
+
+.SH DESCRIPTION
+.PP
+.B opencv_createsamples
+creates positive samples from a single object image or a collection of
+positive images.
+.PP
+The scheme of test samples creation is similar to training samples creation
+since each test sample is a background image into which a randomly
+distorted and randomly scaled instance of the object picture is pasted at a
+random position.
+
+.SH OPTIONS
+.PP
+.B opencv_createsamples
+supports the following options:
+
+.PP
+.TP
+.BI "\-info " collection_file_name
+A database of positive source images. Use it together with
+.B \-img
+to create test samples instead.
+
+.TP
+.BI "\-img " image_file_name
+A positive source image. Use it together with
+.B \-info
+to create test samples instead.
+
+.TP
+.BI "\-vec " vec_file_name
+The output file name containing the generated positive samples for training.
+
+.TP
+.BI "\-bg " background_file_name
+The background description file (the negative sample set). It contains a list
+of images into which randomly distorted versions of the object are pasted for
+positive sample generation.
+
+.TP
+.BI "\-num " number_of_samples
+The number of positive samples to generate/train. The default is
+.IR 1000 .
+
+.TP
+.BI "\-bgcolor " background_color
+The background color (currently grayscale images are assumed); the background
+color denotes the transparent color. The default is
+.IR 0 .
+.\" TODO: What does 0 mean? How are colors expressed with integers?
+
+.TP
+.B \-inv
+Invert the colors.
+.TP
+
+.TP
+.BI "\-maxidev " max_intensity_deviation
+The desired maximum intensity deviation of foreground samples pixels. The
+default is
+.IR 40 .
+
+.TP
+.BI "\-maxxangle " max_x_rotation_angle
+The maximum rotation angle in x-direction in radians. The default is
+.IR 1.1 .
+
+.TP
+.BI "\-maxyangle " max_y_rotation_angle
+The maximum rotation angle in y-direction in radians. The default is 
+.IR 1.1 .
+
+.TP
+.BI "\-maxzangle " max_z_rotation_angle
+The maximum rotation angle in z-direction in radians. The default is 
+.IR 0.5 .
+
+.TP
+.BI "\-show [" scale_factor "]"
+Show each created sample during the creation process. Optionally a scaling
+factor can be defined. The default is
+.IR 4.0 .
+.IP
+If <\fBESC\fR> is pressed, the creation process will continue without showing
+the samples. This can be useful for debugging purposes.
+
+.TP
+.BI "\-h " sample_height
+For the creation of training samples, it is the resulting sample height.
+The default is
+.IR 24 .
+.IP
+In case of creating test samples, it is the minimal height of placed object 
+picture.
+
+.TP
+.BI "\-w " sample_width
+For the creation of training samples, it is the resulting sample width.
+The default is
+.IR 24 .
+.IP
+In case of creating test samples, it is the minimal width of placed object
+picture.
+
+.PP
+The same information is shown, if
+.B opencv_createsamples
+is called without any arguments/options.
+
+
+.SH EXAMPLES
+.PP
+To create training samples from one image applying distortions and show the
+results:
+.IP
+.B opencv_createsamples -img source.png -num 10 -bg negatives.dat -vec samples_out.vec -show
+.PP
+To create training samples of size 40x40 from some images without applying
+distortions:
+.IP
+.B opencv_creasamples -info source.dat -vec samples_out.vec -w 40 -h 40
+
+
+.SH SEE ALSO
+.PP
+.BR opencv_haartraing (1),
+.BR opencv_performance (1)
+.PP
+More information and examples can be found in the OpenCV documentation.
+
+
+.SH AUTHORS
+.PP
+This manual page was written by \fBDaniel Leidert\fR <\&daniel.leidert@wgdd.de\&>
+and \fBNobuhiro Iwamatsu\fR <\&iwamatsu@debian.org\&>
+for the Debian project (but may be used by others).
diff --git a/debian/man/opencv_haartraining.1 b/debian/man/opencv_haartraining.1
new file mode 100644
index 0000000..6f8d090
--- /dev/null
+++ b/debian/man/opencv_haartraining.1
@@ -0,0 +1,215 @@
+.TH "OPENCV_HAARTRAINING" "1" "May 2010" "OpenCV" "User Commands"
+
+
+.SH NAME
+opencv_haartraining \- train classifier
+
+
+.SH SYNOPSIS
+.B opencv_haartraining [options]
+
+
+.SH DESCRIPTION
+.PP
+.B opencv_haartraining
+is training the classifier. While it is running, you can already get an
+impression, whether the classifier will be suitable or if you need to improve
+the training set and/or parameters.
+.PP
+In the output:
+.TP
+.RB \(aq POS: \(aq
+shows the hitrate in the set of training samples (should be equal or near to
+.I 1.0
+as in stage 0)
+.TP
+.RB \(aq NEG: \(aq
+indicates the false alarm rate (should reach at least
+.I 5*10-6
+to be a usable classifier for real world applications)
+.PP
+If one of the above values gets
+.IR 0 " (" zero ")"
+there is an overflow. In this case the false alarm rate is so low, that
+further training doesn't make sense anymore, so it can be stopped.
+
+
+.SH OPTIONS
+.PP
+.B opencv_haartraining
+supports the following options:
+
+.PP
+.TP
+.BI "\-data " dir_name
+The directory in which the trained classifier is stored.
+
+.TP
+.BI "\-vec " vec_file_name
+The file name of the positive samples file (e.g. created by the
+.BR opencv_createsamples (1)
+utility).
+
+.TP
+.BI "\-bg " background_file_name
+The background description file (the negative sample set). It contains a list
+of images into which randomly distorted versions of the object are pasted for
+positive sample generation.
+
+.TP
+.BI "\-bg-vecfile
+This option is that bgfilename represents a vec file with discrete negatives. The default is
+.BR "not set".
+
+.TP
+.BI "\-npos " number_of_positive_samples
+The number of positive samples used in training of each classifier stage.
+The default is
+.IR 2000 .
+
+.TP
+.BI "\-nneg " number_of_negative_samples
+The number of negative samples used in training of each classifier stage.
+The default is
+.IR 2000 .
+
+.PP
+Reasonable values are
+.BR "\-npos 7000 \-nneg 3000" .
+
+.TP
+.BI "\-nstages " number_of_stage
+The number of stages to be trained. The default is
+.IR 14 .
+
+.TP
+.BI "\-nsplits " number_of_splits
+Determine the weak classifier used in stage classifiers. If the value is
+.IP
+.BR 1 ,
+then a simple stump classifier is used
+.IP
+.BR >=2 ,
+then CART classifier with
+.I number_of_splits
+internal (split) nodes is used
+.IP
+The default is
+.IR 1 .
+
+.TP
+.BI "\-mem " memory_in_MB
+Available memory in
+.B MB
+for precalculation. The more memory you have the faster the training process is.
+The default is
+.IR 200 .
+
+.TP
+.B \-sym, \-nonsym
+Specify whether the object class under training has vertical symmetry or not.
+Vertical symmetry speeds up training process and reduces memory usage. For
+instance, frontal faces show off vertical symmetry. The default is
+.BR \-sym .
+
+.TP
+.BI "\-minhitrate " min_hit_rate
+The minimal desired hit rate for each stage classifier. Overall hit rate may
+be estimated as
+.IR "\%min_hit_rate^number_of_stages" .
+The default is
+.IR 0.950000 .
+
+.TP
+.BI "\-maxfalsealarm " max_false_alarm_rate
+The maximal desired false alarm rate for each stage classifier. Overall false
+alarm rate may be estimated as
+.IR "\%max_false_alarm_rate^number_of_stages" .
+The default is
+.IR 0.500000 .
+
+.TP
+.BI "\-weighttrimming " weight_trimming
+Specifies whether and how much weight trimming should be used. The default is
+.IR 0.950000 .
+A decent choice is
+.IR 0.900000 .
+
+.TP
+.B \-eqw
+Specify if initial weights of all samples will be equal.
+
+.TP
+.BI "\-mode {" BASIC | CORE | ALL "}"
+Select the type of haar features set used in training.
+.I BASIC
+uses only upright features, while
+.I CORE
+uses the full upright feature set and
+.I ALL
+uses the full set of upright and 45 degree rotated feature set.
+The default is
+.IR BASIC .
+.IP
+For more information on this see \%http://www.lienhart.de/ICIP2002.pdf.
+
+.TP
+.BI "\-h " sample_height
+The sample height (must have the same value as used during creation).
+The default is
+.IR 24 .
+
+.TP
+.BI "\-w " sample_width
+The sample width (must have the same value as used during creation).
+The default is
+.IR 24 .
+
+.TP
+.BI "\-bt {" DAB | RAB | LB | GAB "}"
+The type of the applied boosting algorithm. You can choose between Discrete
+AdaBoost (\fIDAB\fR), Real AdaBoost (\fIRAB\fR), LogitBoost (\fILB\fR) and
+Gentle AdaBoost (\fIGAB\fR). The default is
+.IR GAB .
+
+.TP
+.BI "\-err {" misclass | gini | entropy "}"
+The type of used error if Discrete AdaBoost (\fB\-bt DAB\fR) algorithm is
+applied. The default is
+.IR misclass .
+
+.TP
+.BI "\-maxtreesplits " max_number_of_splits_in_tree_cascade
+The maximal number of splits in a tree cascade. The default is
+.IR 0 .
+
+.TP
+.BI "\-minpos " min_number_of_positive_samples_per_cluster
+The minimal number of positive samples per cluster. The default is
+.IR 500 .
+
+.PP
+The same information is shown, if
+.B opencv_haartraining
+is called without any arguments/options.
+
+
+.SH EXAMPLES
+.PP
+TODO
+.\" http://robotik.inflomatik.info/other/opencv/OpenCV_ObjectDetection_HowTo.pdf
+
+
+.SH SEE ALSO
+.PP
+.BR opencv_createsamples (1),
+.BR opencv_performance (1)
+.PP
+More information and examples can be found in the OpenCV documentation.
+
+
+.SH AUTHORS
+.PP
+This manual page was written by \fBDaniel Leidert\fR <\&daniel.leidert@wgdd.de\&>
+and \fBNobuhiro Iwamatsu\fR <\&iwamatsu@debian.org\&>
+for the Debian project (but may be used by others).
diff --git a/debian/man/opencv_performance.1 b/debian/man/opencv_performance.1
new file mode 100644
index 0000000..1742921
--- /dev/null
+++ b/debian/man/opencv_performance.1
@@ -0,0 +1,126 @@
+.TH "OPENCV_PERFORMANCE" "1" "May 2010" "OpenCV" "User Commands"
+
+
+.SH NAME
+opencv_performance \- evaluate the performance of the classifier
+
+
+.SH SYNOPSIS
+.B opencv_performance [options]
+
+
+.SH DESCRIPTION
+.PP
+.B opencv_performance
+evaluates the performance of the classifier. It takes a collection of marked
+up test images, applies the classifier and outputs the performance, i.e. number of
+found objects, number of missed objects, number of false alarms and other
+information.
+.PP
+When there is no such collection available test samples may be created from single
+object image by the
+.BR opencv_createsamples (1)
+utility. The scheme of test samples creation in this case is similar to training samples
+.PP
+In the output, the table should be read:
+.TP
+.RB \(aq Hits \(aq
+shows the number of correctly found objects
+.TP
+.RB \(aq Missed \(aq
+shows the number of missed objects (must exist but are not found, also known
+as false negatives)
+.TP
+.RB \(aq False \(aq
+shows the number of false alarms (must not exist but are found, also known
+as false positives)
+
+
+.SH OPTIONS
+.PP
+.B opencv_performance
+supports the following options:
+
+.PP
+
+.TP
+.BI "\-data " classifier_directory_name
+The directory, in which the classifier can be found.
+
+.TP
+.BI "\-info " collection_file_name
+File with test samples description.
+
+.TP
+.BI "\-maxSizeDiff " max_size_difference
+Determine the size criterion of reference and detected coincidence.
+The default is
+.IR 1.500000 .
+
+.TP
+.BI "\-maxPosDiff " max_position_difference
+Determine the position criterion of reference and detected coincidence.
+The default is
+.IR 0.300000 .
+
+.TP
+.BI "\-sf " scale_factor
+Scale the detection window in each iteration. The default is
+.IR 1.200000 .
+
+.TP
+.B \-ni
+Don't save detection result to an image. This could be useful, if
+.I collection_file_name
+contains paths.
+
+.TP
+.BI "\-nos " number_of_stages
+Number of stages to use. The default is
+.I \-1
+(all stages are used).
+
+.TP
+.BI "\-rs " roc_size
+The default is
+.IR \40 .
+
+.TP
+.BI "\-h " sample_height
+The sample height (must have the same value as used during creation).
+The default is
+.IR 24 .
+
+.TP
+.BI "\-w " sample_width
+The sample width (must have the same value as used during creation).
+The default is
+.IR 24 .
+
+.PP
+The same information is shown, if
+.B opencv_performance
+is called without any arguments/options.
+
+
+.SH EXAMPLES
+.PP
+To create training samples from one image applying distortions and show the
+results:
+.IP
+.B opencv_performance -data trainout -info tests.dat
+
+
+.SH SEE ALSO
+.PP
+.BR opencv_createsamples (1),
+.BR opencv_haartraing (1)
+.PP
+More information and examples can be found in the OpenCV documentation.
+
+
+.SH AUTHORS
+.PP
+This manual page was written by \fBDaniel Leidert\fR <\&daniel.leidert@wgdd.de\&>
+and \fBNobuhiro Iwamatsu\fR <\&iwamatsu@debian.org\&>
+for the Debian project (but may be used by others).
diff --git a/debian/man/opencv_traincascade.1 b/debian/man/opencv_traincascade.1
new file mode 100644
index 0000000..b310406
--- /dev/null
+++ b/debian/man/opencv_traincascade.1
@@ -0,0 +1,142 @@
+.TH "OPENCV_TRAINCASCADE" "1" "May 2010" "OpenCV" "User Commands"
+
+
+.SH NAME
+opencv_traincascade \- transcascade application
+
+
+
+.SH SYNOPSIS
+.B opencv_traincascade [options]
+
+
+.SH DESCRIPTION
+.PP
+.B traincascade application.
+
+.SH OPTIONS
+
+.PP
+.B opencv_traincascade
+supports the following options:
+
+.SH BASIC OPTIONS
+
+.TP
+.BI "\-data " cascade_dir_name
+
+.TP  
+.BI "\-vec " vec_file_name
+
+.TP
+.BI "\-bg " background_file_name
+
+.TP
+.BI "\-numPos " number_of_positive_samples
+The default is
+.IR 2000 .
+
+.TP
+.BI "\-numNeg " number_of_negative_samples
+The default is
+.IR 1000 .
+
+.TP
+.BI "\-num " Stages number_of_stages 
+The default is
+.IR 20 .
+
+.TP
+.BI "\-precalcValBufSize " precalculated_vals_buffer_size_in_Mb
+The default is
+.IR 256 .
+
+.TP
+.BI "\-precalcIdxBufSize " precalculated_idxs_buffer_size_in_Mb
+The default is
+.IR 256 .
+
+.TP
+.BI "\-baseFormatSave "
+
+.SH CASCADE OPTIONS
+ 
+.TP
+.BI "\-stageType "
+The default is
+.IR BOOST .
+
+.TP
+.BI "\-featureType "
+Set feature type . You can select HAAR or LBP.
+The default is
+.IR HAAR .
+
+.TP
+.BI "\-w " sampleWidth
+The default is
+.IR 24 .
+
+.TP
+.BI "\-h " sampleHeight
+The default is
+.IR 24 .
+
+.SH BOOST OPTIONS
+
+.TP
+.BI "\-bt {" DAB | RAB | LB | GAB "}"
+The type of the applied boosting algorithm. You can choose between Discrete
+AdaBoost (\fIDAB\fR), Real AdaBoost (\fIRAB\fR), LogitBoost (\fILB\fR) and
+Gentle AdaBoost (\fIGAB\fR). The default is
+.IR GAB .
+
+.TP
+.BI "\-minHitRate " min_hit_rate
+The default is
+.IR 0.995 .
+
+.TP
+.BI "\-maxFalseAlarmRate " max_false_alarm_rate
+The default is
+.IR 0.5 .
+
+.TP
+.BI "\-weightTrimRate " weight_trim_rate
+The default is
+.IR 0.95 .
+
+.TP
+.BI "\-maxDepth " max_depth_of_weak_tree
+The default is
+.IR 1 .
+
+.TP
+.BI "\-maxWeakCount " max_weak_tree_count
+The default is
+.IR 100 .
+
+.SH HAARFEATURE OPTIONS
+
+.TP
+.BI "\-mode " <BASIC | CORE | ALL>
+The type of the applied haarFeature mode. You can choose between \fIBASIC\fR, 
+\fCORE\fR and \fIALL\fR. The default is
+.IR BASIC .
+
+.SH EXAMPLES
+.PP
+TODO
+
+.SH SEE ALSO
+.PP
+.BR opencv_haartraing (1),
+.BR opencv_performance (1)
+.PP
+More information and examples can be found in the OpenCV documentation.
+
+
+.SH AUTHORS
+.PP
+This manual page was written by \fBNobuhiro Iwamatsu\fR <\&iwamatsu@debian.org\&>
+for the Debian project (but may be used by others).