18399563. METHOD, APPARATUS, AND MEDIUM FOR POINT CLOUD CODING simplified abstract (BEIJING BYTEDANCE NETWORK TECHNOLOGY CO., LTD.)
Contents
METHOD, APPARATUS, AND MEDIUM FOR POINT CLOUD CODING
Organization Name
BEIJING BYTEDANCE NETWORK TECHNOLOGY CO., LTD.
Inventor(s)
Kai Zhang of Los Angeles CA (US)
Li Zhang of Los Angeles CA (US)
METHOD, APPARATUS, AND MEDIUM FOR POINT CLOUD CODING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18399563 titled 'METHOD, APPARATUS, AND MEDIUM FOR POINT CLOUD CODING
- Simplified Explanation:**
The patent application describes a method for coding point clouds by classifying target points in a frame based on thresholds and performing the conversion accordingly.
- Key Features and Innovation:**
- Method involves classifying target points in a point cloud sequence frame into classes based on thresholds.
- Utilizes a larger set of thresholds compared to the number of classes for improved accuracy in motion estimation and coding quality.
- Potential Applications:**
This technology can be applied in various fields such as virtual reality, augmented reality, 3D modeling, and autonomous driving systems.
- Problems Solved:**
- Enhances the accuracy of global motion estimation in point cloud coding.
- Improves the overall coding quality of point cloud sequences.
- Benefits:**
- Increased accuracy in motion estimation.
- Enhanced coding quality for point cloud sequences.
- Improved performance in applications like virtual reality and autonomous driving.
- Commercial Applications:**
This technology could be utilized in industries such as entertainment, gaming, automotive, and robotics for efficient point cloud coding and processing.
- Questions about Point Cloud Coding:**
1. How does the method of classifying target points based on thresholds improve coding quality? 2. What are the potential implications of using a larger set of thresholds for classification in point cloud coding?
Original Abstract Submitted
Embodiments of the present disclosure provide a method for point cloud coding. The method comprises: classifying, during a conversion between a current frame of a point cloud sequence and a bitstream of the point cloud sequence, a target point in the current frame into a first set of classes based on a second set of thresholds, the number of thresholds in the second set being larger than the number of classes in the first set; and performing the conversion based on the classification. Compared with the conventional solution, the proposed method can advantageously improve the accuracy of global motion estimation and coding quality.
