* SVM training may now be done using a polynomial kernel instead of an RBF kernel
* added experimental code for using the coefficients instead of hyperplane distances for removing support vectors in FastSvmTraining (code is not used right now)
Merge branch 'master' into tracking
added new app for head tracking
* moved the dependency on FdImage from the tracking apps to the measurement models
Overhaul of libTracking:
* libTracking now has its own classifiers and feature extractors
* the dynamically trained SVMs do not depend on libFeatureDetection anymore
* only the measurement models depend on libFeatureDetection for now
* easy extension by other classifiers and feature extraction algorithms possible
* removed the static SVM stuff from the learning measurement models
* the switching between learning and static is now done within the learning cond
ensation tracker
* removed the learning strategies, the measurement models themselves are responsible for their update from now on
* renamed Learning within classnames to Adaptive
* the measurement models now depend on TrainableClassifier instead of libSVM stuff and training
* added TrainableClassifier to prevend dependencies of measurement models from templates (otherwise they would have been templates, too)
* removed EagerFeatureVector and put its features into FeatureVector which is not an abstract class anymore
* added parameters to PositionDependentMeasurementModel to influence the way the training samples are generated
* added a new training for libSVM classifiers that keeps a fixed amount of positive and negative training examples and keeps the first positive example forever
* the adaptive tracking is much more stable with these changes (but also slower)
very few parameter changes to speed up the tracking
* fixed a problem with FixedSizeLibSvmTraining when no examples are given
* added output possibilities to libImageIO (video and image-directory)
* added WvmClassifier which wraps around a DetectorWVM and creates a temporary FdPatch
* added two-stage classifiers where a feature vector must pass a classifier to be processed with another
* fixed a bug of the SelfLearningMeasurementModel
* fixed the file names in the make list
* fixed the usage output text of headTrackingApp
Merge branch 'master' into tracking