The MIL algorithm trains a classifier in an online manner to separate the object from the background. More...
#include <tracking.hpp>
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struct | Params |
Public Member Functions | |
virtual | ~TrackerMIL () CV_OVERRIDE |
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virtual | ~Tracker () |
virtual CV_WRAP void | init (InputArray image, const Rect &boundingBox)=0 |
Initialize the tracker with a known bounding box that surrounded the target. | |
virtual CV_WRAP bool | update (InputArray image, CV_OUT Rect &boundingBox)=0 |
Update the tracker, find the new most likely bounding box for the target. | |
Static Public Member Functions | |
static CV_WRAP Ptr< TrackerMIL > | create (const TrackerMIL::Params ¶meters=TrackerMIL::Params()) |
Create MIL tracker instance. | |
Protected Member Functions | |
TrackerMIL () | |
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Tracker () | |
The MIL algorithm trains a classifier in an online manner to separate the object from the background.
Multiple Instance Learning avoids the drift problem for a robust tracking. The implementation is based on [MIL] .
Original code can be found here http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml
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Create MIL tracker instance.
parameters | MIL parameters TrackerMIL::Params |