headTracking

C++ implementation for multi-target tracking algorithm from paper Multi-target tracking by learning local-to-global trajectory models.
Using Kalman filter and SVM classifier to generate tracking scores.

Note

• imgSVM class trains/tests SVM classifier through images.
• Tracker is a higher level class including implementation of Kalman Filters and call of imgSVM class.
• cvLib implements methods for updating trackers and for other utilities specific for tracking task.
• cmpLib implements methods of image feature extraction and comparison.
• global.hpp/.cpp keeps intersection of global variables for both imgSVM class and tracking task.

Usage

• ./headTracking /data/gengshan/vid/testMultiTarget.avi y

todo

• use distance to leverage svm score...
• divide updateTracker function
• optimzie display setting... put tracking result in detection result later.

Log

• params: negNum in TrackingObj class.