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Cy-CNN: cylinder convolution based rotation-invariant neural network for point cloud registration

Science China(Information Sciences) 2023年第5期66卷 73-87页

作者： Hengwang ZHAO Zhidong LIANG Yuesheng HE Chunxiang WANG Ming YANG Department of Automation Shanghai Jiao Tong University Research Institute of Robotics Shanghai Jiao Tong University

Point cloud registration is a challenging problem in the condition of large initial misalignments and noises. A major problem encountered in the registration algorithms is the definition of correspondence between two point clouds. Point clouds contain rich geometric information and the same geometric structure implies the same feature even if they are in diferent poses, which motivates us to seek a rotation-invariant feature representation for calculating the correspondence. This work proposes a rotation-invariant neural network for point cloud registration. To acquire rotation-invariant features, we firstly propose a rotationinvariant point cloud representation(RIPR) at the input level. Instead of using the original coordinates,we propose to use point pair features(PPF) and the transformed coordinates in the local reference frame(LRF) to represent a point. Then, we design a new convolution operator named Cylinder-Conv which utilizes the symmetry of cylinder-shaped voxels and the hierarchical geometry information of the surface of3D shapes. By specifying the cylinder-shaped structures and directions, Cylinder-Conv can better capture the local neighborhood geometry of each point and maintain rotation-invariance. Finally, we combine RIPR and Cylinder-Conv to extract normalized rotation-invariant features to generate the correspondence and perform a diferentiable singular value decomposition(SVD) step to estimate the rigid transformation. The proposed network presents state-of-the-art performance on point cloud registration. Experiments show that our method is robust to initial misalignments and noises.

关键词： deep learning point cloud registration rotation invariant computer vision

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Improved rotation invariant Template Matching Method Using Relative Orientation Codes

Improved Rotation Invariant Template Matching Method Using R...

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第三十届中国控制会议

作者： LI Zhonghai~1,LIU Chunyu~1,CUI Jianguo~1,SHEN Weifeng~2 1.School of Automation,Shenyang Aerospace University,Shenyang 110136,P.R.China 2.Hanwang Science and Technology Limited Company,Beijing 100080,P.R.China

＜正＞Orientation code is the quantization of pixel gradient orientation,which is illumination invariant,and has become an important template matching *** order to improve accuracy and real time ability,we present conception of relative orientation code,and design template matching method based on relative orientation *** method first selects candidate target points using relative orientation codes histogram matching,then calculate the rotation angle of candidate subimage and rotate the sub image,finally match the relative orientation codes in the sub *** experiment show that this method is robust when the image is rotated by any angle,and the candidate points are selected and matched accurately,and the computing time is less than original method.

关键词： Orientation Code rotation invariant Template Matching Histogram Matching

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Three dimensional（3-D） object recogniton with rotation-invariant

Three dimensional（3-D） object recogniton with rotation-inv...

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20th Congress of the International Commission for Optics

作者： LV Jing. and SU Xianyu. Opto-Electronic Department Sichuan University Chengdu China

An automatic method for rotation-invariant three-dimensional (3-D) object recognition is proposed. The method is based on the use of 3-D information contained in the deformed fringe pattern obtained w

关键词： 3-D object recognition rotation invariant multi-channel filter structured light

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