METHOD AND APPARATUS FOR PROCESSING POINT CLOUD DATA

• US 20180075666A1
• Filed: 01/19/2017
• Published: 03/15/2018
• Est. Priority Date: 09/14/2016
• Status: Active Grant

• Current Assignee: Beijing Baidu Netcom Science and Technology Company Limited (Baidu Incorporated)
• Original Assignee: Beijing Baidu Netcom Science and Technology Company Limited (Baidu Incorporated)
• Inventors: Feng, Kaiwen, Chen, Zhuo, Liu, Bocong, Deng, Chengliang, Liang, Yibing, Ma, Yu
• Granted Patent: US 10,460,172 B2
• Time in Patent Office: Days
• CPC Class Codes: G06T 19/00 Manipulating 3D models or images for computer graphics
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2219/004 Annotating, labelling
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 2201/12 Acquisition of 3D measurements of objects

Abstract

The present application discloses a method and an apparatus for processing point cloud data. The method of an embodiment comprises: recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result; presenting the recognition result as an initial labeling result of the point cloud frame; and updating the labeling result in response to a correction operation by a user on the labeling result. According to the embodiment, the speed and accuracy of point cloud data labeling are improved.

Claims

1. A method for processing point cloud data, comprising:

recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result;

presenting the recognition result as an initial labeling result of the point cloud frame; and

updating the labeling result in response to a correction operation by a user on the labeling result.

2. The method according to claim 1, wherein the presenting the recognition result as an initial labeling result of the point cloud frame comprises:

adding a border to a recognized object in the point cloud frame; and

presenting object type information recognized for the recognized object.

3. The method according to claim 2, wherein the updating the labeling result in response to a correction operation by a user on the labeling result comprises:

updating, in response to an adjusting operation by the user on the border, the labeling result according to the adjusted border.

4. The method according to claim 3, wherein the updating the labeling result in response to a correction operation by a user on the labeling result further comprises:

updating, in response to a checking operation by the user on the object type information, the labeling result according to the checked object type information.

5. The method according to claim 1, further comprising:

training the obstacle recognition algorithm by using the updated labeling result as sample data, to update the obstacle recognition algorithm.

6. The method according to claim 5, wherein after the training the obstacle recognition algorithm by using the updated labeling result as sample data, to update the obstacle recognition algorithm, the method further comprises:

recognizing the object in the to-be-recognized point cloud frame by using the updated obstacle recognition algorithm.

7. An apparatus for processing point cloud data, comprising:

at least one processor; and

a memory storing instructions, which when executed by the at least one processor, cause the at least one processor to perform operations, the operations comprising;

recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result;

presenting the recognition result as an initial labeling result of the point cloud frame; and

updating the labeling result in response to a correction operation by a user on the labeling result.

8. The apparatus according to claim 7, wherein the presenting the recognition result as an initial labeling result of the point cloud frame comprises:

adding a border to a recognized object in the point cloud frame; and

presenting object type information recognized for the recognized object.

9. The apparatus according to claim 8, wherein the updating the labeling result in response to a correction operation by a user on the labeling result comprises:

updating, in response to an adjusting operation of the user on the border, the labeling result according to the adjusted border.

10. The apparatus according to claim 9, wherein the updating the labeling result in response to a correction operation by a user on the labeling result further comprises:

updating, in response to a checking operation of the user on the object type information, the labeling result according to the checked object type information.

11. The apparatus according to claim 7, wherein the operations further comprise:

training the obstacle recognition algorithm by using the updated labeling result as sample data, to update the obstacle recognition algorithm.

12. The apparatus according to claim 11, wherein the operations further comprise:

recognizing the object in the to-be-recognized point cloud frame by using the updated obstacle recognition algorithm.

13. A non-transitory storage medium storing one or more programs, the one or more programs when executed by an apparatus, causing the apparatus to perform a method for processing point cloud data, comprising:

recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result;

presenting the recognition result as an initial labeling result of the point cloud frame; and

updating the labeling result in response to a correction operation by a user on the labeling result.