View source for 18598553. SYSTEM AND METHOD FOR PROPOSAL-FREE AND CLUSTER-FREE PANOPTIC SEGMENTATION SYSTEM OF POINT CLOUDS simplified abstract (Huawei Technologies Co., Ltd.)

=SYSTEM AND METHOD FOR PROPOSAL-FREE AND CLUSTER-FREE PANOPTIC SEGMENTATION SYSTEM OF POINT CLOUDS=


==Organization Name==

[[:Category:Huawei Technologies Co., Ltd.|Huawei Technologies Co., Ltd.]]


[[Category:Huawei Technologies Co., Ltd.]]

==Inventor(s)==

[[:Category:THOMAS ENXU Li of Mississauga (CA)|THOMAS ENXU Li of Mississauga (CA)]][[Category:THOMAS ENXU Li of Mississauga (CA)]]

[[:Category:RYAN Razani of Toronto (ON)|RYAN Razani of Toronto (ON)]][[Category:RYAN Razani of Toronto (ON)]]

[[:Category:BINGBING Liu of Markham (CA)|BINGBING Liu of Markham (CA)]][[Category:BINGBING Liu of Markham (CA)]]

==SYSTEM AND METHOD FOR PROPOSAL-FREE AND CLUSTER-FREE PANOPTIC SEGMENTATION SYSTEM OF POINT CLOUDS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18598553 titled 'SYSTEM AND METHOD FOR PROPOSAL-FREE AND CLUSTER-FREE PANOPTIC SEGMENTATION SYSTEM OF POINT CLOUDS

**Simplified Explanation:**
This patent application describes systems and methods for segmenting a point cloud by projecting it into a range image, extracting features, downsampling the feature map, and semantically segmenting the point cloud based on the extracted features.

**Key Features and Innovation:**
* Projection of point cloud into a range image
* Extraction of features from the range image
* Generation of a feature map from the extracted features
* Downscaling of the feature map with scaling based on local geometry
* Semantically segmenting the point cloud based on the extracted features

**Potential Applications:**
* Autonomous driving systems
* Robotics
* Augmented reality
* 3D mapping and modeling

**Problems Solved:**
* Efficient segmentation of point clouds
* Improved understanding of spatial data
* Enhanced object recognition in complex environments

**Benefits:**
* Enhanced accuracy in object segmentation
* Improved performance in object recognition tasks
* Increased efficiency in processing point cloud data

**Commercial Applications:**
* "Advanced Point Cloud Segmentation Technology for Autonomous Vehicles and Robotics"

**Prior Art:**
Prior art related to this technology may include research on point cloud segmentation methods, feature extraction techniques, and downsampling algorithms in the field of computer vision and machine learning.

**Frequently Updated Research:**
Researchers are continually exploring new methods for improving point cloud segmentation accuracy, feature extraction efficiency, and downsampling techniques to enhance the performance of systems like those described in this patent application.

**Questions about Point Cloud Segmentation:**
1. How does downsampling the feature map improve the segmentation of point clouds?
2. What are the potential challenges in implementing this technology in real-world applications?


==Original Abstract Submitted==

Systems and methods for panoptic segmentation of a point cloud are provided. A point cloud is projected into a range image. Features are extracted from the range image and generating a feature map from the extracted features. The feature map is downsampled and the features are scaled during downsampling using local geometry. Features are extracted from the downsampled feature map. The point cloud is semantically segmented at least partially based on the features extracted. Instances in the point cloud are segmented at least partially based on the features extracted.



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