visualization and evaluation of mixture of Gaussian function
changed implementation of water classifier to mixture of Gaussians
added Kalman process model (in SwimmerTracker) to depend on FPS (frames per second)
zeroing swimmer's velocity near pool boundary (to avoid Kalman Filter predicting position beyond pool boundary)
color appearance model experiments (Luv, histogram back projection, mixture of Gaussians)
addded GMM training in batch mode
changed swimmer's tracker to find correspondence TrackedObject~detection based on GMM appearance model
dependency declaration
fixed calculation of bounding box for shape
added an initial version of pool boundary and lane dividers into tracker
added lazy training of GMM for appearance model;
perf: appearance model GMM is evaluated using Matlab routines
perf: reduced load of water mask evaluation
restoring GMM appearance model to OpenCV implementation (EM.predict) due to bug in PixelsClassifier.evalMixGaussians()
added more precise bounds on unassigned tracks cost (for tracker stability)
Merge branch 'develop'