Closed kaiwangntu closed 7 years ago
Hi, Let me respond inline:
1) Yes, all the meshes are reconstructed, including the RGB mesh. 2) Check out this fly-though video. The points are sampled quite densely, and there are many annotations for each face. We use these points to annotate each face (and we don't annotate individual vertices).
HI Alex,
1) Yes. Matterport provides a 3D mesh which is reconstructed from the various camera sweeps in each building. Matterport also provides the RGB textures for this mesh.
2) Your former guess is correct. The only difference between the semantic and RGB meshes is that the semantic textures contain the semantic label. The mesh geometry still comes directly from Matterport, and I believe that they reconstruct it from the sensor depthmaps (which are not included in the released dataset).
Did you mean the RGB/semantic mesh geometry in the dataset provided is just the one reconstructed directly from Matterport? If only parts of the vertices of the Matterport output mesh, i.e. the vertices correspond to the sampled point cloud, are annotated, how did you compute the semantic information of the remaining vertices pls (as you said 'the mesh geometry still comes directly from Matterport')?
Yes, exactly. Regarding how we labeled the mesh: we labeled the faces by projecting the points from the pointcloud onto the mesh. The face label is the majority class of the projected points. Since the faces are the parts that are labeled, it the "class of a vertex" isn't well-defined because a vertex can be a part of multiple faces.
Got it! Thanks for your detailed explanation Alex!
Hi, According to the paper, the point cloud is obtained by sampling the reconstructed mesh and then annotated. So,