Adaptive Point Cloud Streaming for Bandwidth-Limited 3D Visualization
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Solution Overview
Problem
Existing adaptive streaming techniques fail to efficiently transfer original 3D content over data networks with variable conditions and resource availability, necessitating new methods for streaming three-dimensional data in its original form.
Innovation Solution
Adaptive point cloud streaming system that selectively streams points representing important features of a 3D object out-of-order, conserving bandwidth by transmitting a dynamically selected subset of points with positional data and optionally minimal color information, followed by additional data if resources permit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If original 3D point cloud data is streamed over data networks with variable network conditions, then the receiving device can obtain complete 3D content data, but the bandwidth consumption and transmission time increase significantly
Solution Approach 1:
The patent segments the point cloud data into multiple layers or groups of points with different levels of importance. Each segment can be transmitted independently, allowing the receiver to reconstruct 3D content with varying degrees of completeness based on available bandwidth. This resolves the contradiction by enabling complete data transmission when bandwidth is abundant while allowing selective transmission of critical segments when bandwidth is constrained.
Solution Approach 2:
The patent extracts and prioritizes transmission of essential points that define the core structure and important features of 3D objects. By separating critical points from less important points, the system ensures that even with limited bandwidth, the most important 3D content information is transmitted first, reducing bandwidth consumption while maintaining essential data completeness.
2Manufacturing precision
If all points of a point cloud are transmitted to represent important features, then the visualization accuracy is high, but the transmission time and bandwidth usage increase
Solution Approach 1:
The patent applies local quality by transmitting high-density point data only for regions containing important features or details, while using lower density for less critical regions. This allows high visualization accuracy for important features to be achieved without transmitting all points at high density, thereby reducing overall transmission time and bandwidth usage.
Solution Approach 2:
The patent transmits a subset of points that are sufficient to represent important features accurately, rather than transmitting all points. By identifying and transmitting only the necessary points for feature representation, the system achieves adequate visualization accuracy with reduced transmission time.
3Loss of energy
If adaptive streaming techniques are applied to 3D content by converting to 2D images, then bandwidth can be optimized, but the original 3D data cannot be obtained at the receiving device
Solution Approach 1:
The patent implements dynamic adaptive streaming where the transmission strategy for 3D point cloud data adjusts in real-time based on network conditions and client device capabilities. The system can dynamically select between transmitting compressed representations or selective subsets of original 3D points, enabling bandwidth optimization while preserving the ability to deliver original 3D data when needed.
Solution Approach 2:
The patent changes transmission parameters such as point density, data precision, and compression level based on network conditions and client requirements. By adjusting these parameters dynamically, the system optimizes bandwidth usage while maintaining the capability to transmit original 3D content data when high fidelity is required.
4Loss of energy
If a dynamically selected subset of points is streamed to conserve bandwidth, then bandwidth usage is reduced, but complete visualization of the 3D object cannot be achieved
Solution Approach 1:
The patent performs preliminary analysis and classification of points to identify important features and critical points before transmission. This preliminary action enables the system to prioritize and transmit essential points first, allowing bandwidth conservation while ensuring that the most important visual information is delivered even if complete visualization cannot be achieved immediately.
Solution Approach 2:
The patent implements feedback mechanisms where the receiving device communicates back to the transmitting device about rendering needs, missing information, and client device capabilities. This feedback enables dynamic adjustment of subsequent transmissions to supplement the initial subset, progressively improving visualization completeness while maintaining bandwidth efficiency.
Data Source
AI summary
A streaming system and associated methods provide adaptive streaming of point cloud data for out-of-order presentation of important visual features before less important visual features. The adaptive streaming includes retrieving the points for a requested point cloud, differentiating different sets of points that represent different features in the point cloud, prioritizing each set of points based on a feature that is represented by that set of points, and streaming the different sets of points across a data network to a client device in an order that is determined from the prioritization. Moreover, the adaptive streaming may dynamically select a different subset of points from each set of points and different subset of point data to stream with each selected subset of points to visually convey important detail of each feature without all the corresponding points or data that make up that feature in the point cloud.