3D点云匹配
我有一个 3D 点云，我想将不同的点云相互匹配以进行识别。 OpenCV 或 Tensorflow 可以帮我实现吗？如果是，怎么办？
示例：
src1 = pointCloud of object 1
src2 = pointCloud of object 2
compare(src1, src2)
输出：两个点云属于同一对象或不同对象。
我想要实现这样的目标。请提供一些想法或资源帮助。
I have a 3D point cloud and I would like to match different point clouds with each other for recognition purposes. Does OpenCV or Tensorflow do it for me? if yes, how?
Example:
src1 = pointCloud of object 1
src2 = pointCloud of object 2
compare(src1, src2)
Output: Both point clouds are of the same object or different objects.
I want to achieve something like this. Please help with some ideas or resources.
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OpenCV 表面匹配可用于检测和查找另一个点云中给定点云的姿态。
Open3d 中有一个 3D 重建模块，但它用于注册（查找姿势）RGBD 图像并从中重建 3D 对象。但是有一个子步骤，其中注册不同的点云片段（查找点云的姿态）以将它们组合成单个点云以进行重建。但不确定它对您的任务是否有用。
有许多 3d 点云对象检测方法也使用神经网络，但如果您的对象在标准数据集中不可用，则必须生成训练所需的数据。
OpenCV Surface Matching can be used to detect and find pose of a given point cloud within another point cloud.
In Open3d there is a 3d reconstruction module, but it is used to register (find poses) of RGBD Images and reconstruct 3d object from them. But there is a sub step in which different point cloud fragments are registered (finding pose of point clouds) to combine them into a single point cloud for reconstruction. But not sure if it is useful for your task.
There are many 3d Point cloud object detection methods which use neural networks, as well, but you have to generate the data needed to train, if your objects are not available in a standard dataset.