ICIP 2006, Atlanta, GA

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Paper Detail

Session:Motion Detection and Estimation
Time:Monday, October 9, 14:20 - 17:00
Presentation: Poster
Topic: Motion Detection and Estimation: Parametric models for motion estimation
Authors: Alex Rav-Acha; The Hebrew University of Jerusalem 
 Shmuel Peleg; The Hebrew University of Jerusalem 
Abstract: Many methods for motion computation and object tracking are based on the Lucas-Kanade (LK) framework. 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.