July 2015
Intermediate to advanced
216 pages
4h 37m
English
Content preview from Mastering OpenCV Android Application ProgrammingBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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The Kanade-Lucas-Tomasi tracker
Having seen local and global motion estimation, we will now take a look at object tracking. Tracking objects is one of the most important applications of computer vision. The Kanade-Lucas-Tomasi (KLT) tracker implements an optical flow to track objects in videos. The steps to implement the algorithm are explained as follows:
- Detect Harris corners in the first frame of the video.
- For each detected Harris corner, compute the motion between consecutive frames using the optical flow (translator) and local affine transformation (affine).
- Now link these motion vectors from frame-to-frame to track the corners.
- Generate new Harris corners after a specific number of frames (say, 10 to 20) to compensate for new points entering ...
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