|IMU-Assisted KLT Feature Tracker
The KLT (Kanade-Lucas-Tomasi) method seeks to increase the robustness of feature tracking utilities by tracking a set of feature points in an image sequence. Our goal is to enhance the KLT method to increase the number of feature points and their tracking length under real-time constraint.
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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