Conference Proceeding

A kind of global motion estimation algorithm based on feature matching

Coll. of Autom., Harbin Eng. Univ., Harbin, China
09/2009; DOI:10.1109/ICMA.2009.5246379 In proceeding of: Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Source: IEEE Xplore

ABSTRACT In this paper, we propose a kind of global motion estimation algorithm based on feature matching. The scale invariant feature transform (SIFT) algorithm is applied to global motion estimation. The feature extracted by SIFT algorithm is invariant to image scale and rotation. The matching accuracy is very high even under the condition of additive noise, varying illumination and affine deformation. It is advantageous to get precise estimation. But the feature of local motion is disadvantageous for global motion estimation. In order to improve the accuracy of global motion estimation, an adaptive noise reduction algorithm is presented to eliminate local motion. The parameters of the camera affine model are computed by the least square method. The proposed algorithm is tested by the standard image sequences and compared with other related methods. The experiments show that the proposed algorithm is adaptive and more accurate.

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Keywords

adaptive noise reduction algorithm
 
additive noise
 
camera affine model
 
global motion estimation
 
global motion estimation algorithm
 
image scale
 
local motion
 
matching accuracy
 
proposed algorithm
 
related methods
 
scale invariant feature
 
SIFT
 
SIFT algorithm
 
square method
 
standard image sequences
 
varying illumination