Device for transmitting point cloud data, method for transmitting point cloud data, device for receiving point cloud data, and method for receiving point cloud data

1. A method of transmitting point cloud data, the method comprising:

encoding the point cloud data,

wherein the encoding includes:

generating levels of detail (LoDs) for the point cloud data,

generating refinement lists including refinement points for the levels of detail,

predicting a point in the refinement lists for a current level of detail by searching a neighboring point,

wherein the point is predicted based on the refinement lists for a reference level of detail which is fewer than a total number of the levels of detail; and

transmitting a bitstream including the point cloud data and signaling information.

2. The method of claim 1 ,

wherein the searching the neighboring point is performed in a refined group,

wherein the encoding further includes generating residual information based on the predicted point.

3. The method of claim 2 ,

wherein the searching the neighboring point is performed in a same or another refined group in the level of detail,

wherein the level of detail represents a set of points spaced apart by a distance shorter than a sampling distance corresponding to each level,

wherein a refined group represents, for each level, a group of points corresponding to a difference between a current level of the level of detail and a next level of the level of detail.

4. The method of claim 3 , wherein the predicting includes:

predicting the point using a prediction tree representing an adjacency relationship between the points.

5. The method of claim 3 , wherein:

a parent of points in a refined group of a first level is one of points included in the refined group of the first level; or

the parent of the points in the refined group of the first level is one of points included in a refined group of a second level; or

the parent of the points in the refined group of the first level is one of points included in an LOD group of the first level.

6. The method according to claim 2 , wherein the signaling information includes:

information representing a method for generating the LoD; and

information representing a method for the prediction.

7. The method of claim 2 , wherein the predicting includes:

determining an adjacency relationship by searching for the points in order of distances with respect to at least one of the points, elevation angles with respect to the points, or azimuth angles with respect to the points.

8. A device for transmitting point cloud data, the device comprising:

an encoder configured to encode point cloud data,

wherein the encoder is configured to:

generate levels of detail (LoDs) for the point cloud data,

generate refinement lists including refinement points for the levels of detail,

predict a point the refinement lists for a current level of detail by searching a neighboring point,

wherein the point is predicted based on the refinement lists for a reference level of detail which is fewer than a total number of the levels of detail; and

a transmitter configured to transmit a bitstream including the point cloud data and signaling information.

9. The device of claim 8 , wherein the encoder is configured to:

search the neighboring point in a same refined group or another refined group in the level of detail, and

generate residual information based on the predicted point,

wherein the level of detail represents a set of points spaced apart by a distance shorter than a sampling distance corresponding to each level,

wherein a refined group represents, for each level, a group of points corresponding to a difference between a current level of the level of detail and a next level of the level of detail.

10. The device of claim 9 , wherein the encoder configured to predict the point using a prediction tree representing an adjacency relationship between the points,

wherein:

a parent of points in a refined group of a first level is one of points included in the refined group of the first level; or

the parent of the points in the refined group of the first level is one of points included in a refined group of a second level; or

the parent of the points in the refined group of the first level is one of points included in an LOD group of the first level.

11. The device according to claim 9 , wherein the signaling information includes information representing a method for generating the level of detail and information representing a method for the prediction,

wherein the predictor is configured to determine an adjacency relationship by searching for the points in order of distances with respect to at least one of the points, elevation angles with respect to the points, or azimuth angles with respect to the points.

12. A method of receiving point cloud data, the method comprising:

receiving a bitstream including point cloud data and signaling information;

decoding the point cloud data,

wherein the decoding includes:

generating levels of detail (LoDs) for the point cloud data, and

generating refinement lists including refinement points for the levels of detail,

predicting a point in the refinement lists for a current level of detail by searching a neighboring point,

wherein the point is predicted based on the refinement lists for a reference level of detail which is fewer than a total number of the levels of detail.

13. The method of claim 12 ,

wherein the searching the neighboring point is performed in a same group or another refined group in the level of detail,

wherein the level of detail represents a set of points spaced apart by a distance shorter than a sampling distance corresponding to each level,

wherein a refined group represents, for each level, a group of points corresponding to a difference between a current level of the level of detail and a next level of the level of detail

wherein the decoding further includes:

reconstructing the point cloud data based on the prediction.

14. The method of claim 13 , wherein the prediction includes:

predicting the geometry data about the points using a prediction tree representing an adjacency relationship.

15. A device for receiving point cloud data, the device comprising:

a receiver configured to receive a bitstream including point cloud data and signaling information;

a decoder configured to decode the point cloud data,

wherein the decoder is configured to:

generate levels of detail (LoDs) for the point cloud data, and

generate refinement lists including refinement points for the levels of detail,

predict a point in the refinement lists for a current level of detail by searching a neighboring point,

wherein the point is predicted based on the refinement lists for a reference level of detail which is fewer than a total number of the levels of detail.