Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 3D point cloud data is used for 3D model acquisition, geometry processing and 3D inspection. Registration of#R##N##R##N#3D point cloud data is crucial for each field. The difference beten 2D image registration and 3D point cloud#R##N##R##N#registration is that the latter requires several things to be considered: translation on each plane, rotation, tilt#R##N##R##N#and etc.  describes a method of registering 3D point cloud data with noise. The relationship beten#R##N##R##N#the two sets of 3D point cloud data can be obtained by Affine transformation. In order to calculate 3D Affine#R##N##R##N#transformation matrix, corresponding points are required. To find the corresponding points,  use the height#R##N##R##N#map which is projected from 3D point cloud data onto XY plane.  formulate the height map matching as a#R##N##R##N#cost function and estimate the corresponding points. To find the proper 3D Affine transformation matrix, #R##N##R##N#formulate a cost function which uses the relationship of the corresponding points. Also the proper 3D Affine#R##N##R##N#transformation matrix can be calculated by minimizing the cost function. The experimental results show that#R##N##R##N#the proposed method can be applied to various objects and gives better performance than the previous work.
['Sungho Suh', 'Hansang Cho', 'Donglok Kim']
I am writing a research paper on a idea Robust Registration Method of 3D Point Cloud Data
[{"from": "human", "value": "I am writing a research paper on a idea Robust Registration Method of 3D Point Cloud Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 3D point cloud data is used for 3D model acquisition, geometry processing and 3D inspection. Registration of#R##N##R##N#3D point cloud data is crucial for each field. The difference beten 2D image registration and 3D point cloud#R##N##R##N#registration is that the latter requires several things to be considered: translation on each plane, rotation, tilt#R##N##R##N#and etc.  describes a method of registering 3D point cloud data with noise. The relationship beten#R##N##R##N#the two sets of 3D point cloud data can be obtained by Affine transformation. In order to calculate 3D Affine#R##N##R##N#transformation matrix, corresponding points are required. To find the corresponding points,  use the height#R##N##R##N#map which is projected from 3D point cloud data onto XY plane.  formulate the height map matching as a#R##N##R##N#cost function and estimate the corresponding points. To find the proper 3D Affine transformation matrix, #R##N##R##N#formulate a cost function which uses the relationship of the corresponding points. Also the proper 3D Affine#R##N##R##N#transformation matrix can be calculated by minimizing the cost function. The experimental results show that#R##N##R##N#the proposed method can be applied to various objects and gives better performance than the previous work."}]