This pullrequest changes

This pullrequest adds a tracker that uses Tracking-by-Matching approach.

The approach uses two different appearance measures to compute affinity between bounding boxes:
some fast descriptor and some strong descriptor. Each time the assignment
problem is solved. The assignment problem in our case is how to establish
correspondence between existing tracklets and recently detected objects.
First step is to compute an affinity matrix between tracklets and
detections. The affinity equals to
appearance_affinity * motion_affinity * shape_affinity.
Where appearance is 1 - distance(tracklet_fast_dscr, detection_fast_dscr).
Second step is to solve the assignment problem using Kuhn-Munkres
algorithm. If correspondence between some tracklet and detection is
established with low confidence (affinity) then the strong descriptor is
used to determine if there is correspondence between tracklet and detection.