Motion parameter evaluation, camera calibration and surface code generation using computer vision
This research focuses on evaluation of motion parameters, Camera calibration and surface code generation using camera acquired images. The motion parameters of a moving object are studied using a static camera. Camera calibration is done by observing four non-coplanar static points, known in space. The principles of distance invariance between rigid points and angular invariance between fixed lines are used in the method developed to accomplish the goal. Because of the loss of the depth information in a 2-D image of a 3-D scene, each point in space contributes one unknown. The equations formulated are solved using the IMSL subroutine ZSPOW. The evaluated unknowns are used to compute the position in space which are subsequently utilized in the estimation of motion parameters and Camera calibration. The method benefits when the actual distance between points of observation is known in advance. Surface code is an object identifying feature. This may be used as an identifying feature for object recognition purposes. The code developed is simple, orientation independent and computationally faster. Considering the error contributing factors in locating image points, camera distortions and measurements of actual distances the computed results compare favorably with actual values in case of motion estimation and Camera calibration. The surface codes for all the images worked with have been generated successfully. The results indicate that the method is practically feasible.
School Location:USA - Ohio
Source Type:Master's Thesis
Keywords:motion parameter evaluation camera calibration surface code generation computer vision
Date of Publication:01/01/1989