Notice of Violation of IEEE Publication Principles: Motion Vector Estimation of Video Image by Pyramidal Implementation of Lucas Kanade Optical Flow

Notice of Violation of IEEE Publication Principles

"Motion vector estimation of video image by Pyramidal implementation of Lucas Kanade Optical flow"
by Sukeshini N.Tamgade and Vibha R. Bora
in the Proceedings of the 2nd International Conference on Emerging Trends in Engineering and Technology (ICETET), January 2009, pp.914-917

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper duplicates content from the paper cited below. The original content was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"Pyramidal Implementation of the Affine Lucas Kanade Feature Tracker Description of the Algorithm"
by Jean-Yves Bouguet
in Intel Corporation-Microprocessor Research Labs Report, January 2001


Motion vector estimation is an important parameter for video segmentation. Effective video compression can be achieved by choosing a correct approach for the calculation of motion vector. Here in this paper we propose an optical flow motion vector estimation through iterative Lucas-Kanade Pyramidal implementation for both large & small motion In image pyramid representation a group of pixel information is gradually reduced to a value of one pixel information for both current & reference frame. The velocity & displacement at each pixel is obtained by using Lucas-Kanade equations. The original image is recovered by warping reference frame towards current frame using flow vectors i.e. velocity & displacement by using image warping techniques. The process is repeated until convergence. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences.