（探戈项目）点云的旋转和平移与区域学习

问题描述

我有一个java应用程序，当我按下按钮时，记录点云xyz坐标和正确的姿势。

I have a java application that, when I press a button, records point clouds xyz coordinates together with the right pose.

我想要的是选择一个对象，记录前面的一个pointCloud和后面的一个，然后合并2个云。

What I want is to pick an object, record a pointCloud in the front and one in the back, then merge the 2 clouds.

显然，要获得合理的结果，我需要翻译并旋转其中一个或两个我记录的云。但我是Tango Project的新手，有一些我不应该错过的东西。

Obviously to get a reasonable result I need to translate and rotate one or both the clouds I recorded. But I'm new to Tango Project and there are some things I should be missing.

我已经在。

在那里，@ Jason Guo讨论那些矩阵：

There, @Jason Guo talks about those matrix:

• 我怎么能得到它们？


• 我应该使用？



第一个矩阵是从服务开始到设备，但我正在使用区域学习，所以我的BaseFrame是 TangoPoseData.COORDINATE_FRAME_AREA_DESCRIPTION 。

The first matrix is from start of service to device, but I'm using area learning, so my BaseFrame is TangoPoseData.COORDINATE_FRAME_AREA_DESCRIPTION.



• 在我的情况下是否也可以使用相同的策略？


• 只需用 area_description_T_device ？
$替换 start_service_T_device b $ b

我想扩展这种方法来进行物体的3D重建。 >
我想获得几个相同对象的不同视图的pointCloud，旋转并将它们转换成一些固定的轴。然后我假设如果x~ = x'&&和2'（x，y，z）和（x'，y'，z'）是相同的点。 y~ = y'&& z~ = z'。

这样我就能够得到整个物体的点云，对吗？

I want to extend this approach for the 3D reconstruction of objects.
I want to get several pointClouds of different view of the same object, rotate and translate them wrf some fixed axes. Then i'll assume that 2 points (x,y,z) and (x',y',z') are the same point if x~=x' && y~=y' && z~=z'.
This way i'll should be able to get a point cloud of the entire object, am I right?



• 这种做法是否合适？


• 有更好的选择吗？



推荐答案

原帖有点过时了。以前，我们没有来查询每个转换，然后使用矩阵将它们链接起来。

The original post is a little bit out of date. Previously, we don't have getMatrixTransformAtTime(). So you have to use Tango.getPoseAtTime to query each of the transformation, and then chain them up using matrix.

但现在，使用getMatrixTransformAtTime，您可以直接查询area_description_T_depth，即使在opengl帧中也是如此。为了将点云转换为opengl中的ADF帧，您可以使用以下代码（伪代码）：

But now, with getMatrixTransformAtTime, you can directly query area_description_T_depth, even in opengl frame. In order to transform a point cloud to the ADF frame in opengl, you can use following code (pseudo code):

TangoSupport.TangoMatrixTransformData transform =
  TangoSupport.getMatrixTransformAtTime(pointCloud.timestamp,
          TangoPoseData.COORDINATE_FRAME_START_OF_SERVICE,
          TangoPoseData.COORDINATE_FRAME_CAMERA_DEPTH,
          TangoSupport.TANGO_SUPPORT_ENGINE_OPENGL,
          TangoSupport.TANGO_SUPPORT_ENGINE_TANGO);

// Convert it into the matrix format you use in render.
// This is a pure data structure conversion, transform is
// in opengl world frame already.
Matrix4x4 model_matrix = ConvertMatrix(transform);

foreach (Point p in pointCloud) {
  p = model_matrix * p;
}

// Now p is in opengl world frame.

但请注意，您必须拥有有效的区域描述框架才能根据区域描述查询姿势，即在使用ADF重新定位或处于学习模式之后。

But note that, you have to have a valid area description frame to query the pose based on area description, that is after relocalized with an ADF or in learning mode.

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