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ICIP
2006
IEEE

Lucas-Kanade without Iterative Warping

15 years 2 months ago
Lucas-Kanade without Iterative Warping
Many methods for motion computation and object tracking are based on the Lucas-Kanade (LK) framework [1]. We present a method which substantially speeds up the LK approach while preserving its accuracy. This acceleration is obtained by avoiding the iterative image warping, inherent to the LK framework. A three-fold speedup is observed on standard image alignment tasks. Our second contribution focuses on adopting a multi-frame approach in order to increase alignment accuracy and robustness. By utilizing the acceleration procedure, the complexity of this multi-frame alignment becomes comparable to that of the two-frame approach.
Alex Rav-Acha, Shmuel Peleg
Added 22 Oct 2009
Updated 22 Oct 2009
Type Conference
Year 2006
Where ICIP
Authors Alex Rav-Acha, Shmuel Peleg
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