Sensors 2012, 12(9), 12694-12709; doi:10.3390/s120912694
Article

Optimal Filter Estimation for Lucas-Kanade Optical Flow

email and * email
Received: 7 June 2012; in revised form: 3 September 2012 / Accepted: 4 September 2012 / Published: 17 September 2012
(This article belongs to the Section Physical Sensors)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filtering approach as a pre-processing step for the Lucas-Kanade pyramidal optical flow algorithm. Based on a study of different types of filtering methods and applied on the Iterative Refined Lucas-Kanade, we have concluded on the best filtering practice. As the Gaussian smoothing filter was selected, an empirical approach for the Gaussian variance estimation was introduced. Tested on the Middlebury image sequences, a correlation between the image intensity value and the standard deviation value of the Gaussian function was established. Finally, we have found that our selection method offers a better performance for the Lucas-Kanade optical flow algorithm.
Keywords: optical flow; Lucas-Kanade; Gaussian filtering; optimal filtering
PDF Full-text Download PDF Full-Text [479 KB, uploaded 21 June 2014 04:38 CEST]

Export to BibTeX |
EndNote


MDPI and ACS Style

Sharmin, N.; Brad, R. Optimal Filter Estimation for Lucas-Kanade Optical Flow. Sensors 2012, 12, 12694-12709.

AMA Style

Sharmin N, Brad R. Optimal Filter Estimation for Lucas-Kanade Optical Flow. Sensors. 2012; 12(9):12694-12709.

Chicago/Turabian Style

Sharmin, Nusrat; Brad, Remus. 2012. "Optimal Filter Estimation for Lucas-Kanade Optical Flow." Sensors 12, no. 9: 12694-12709.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert