3D Point Cloud Pipeline for Accurate Video-Depth Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional multimedia and AI pipelines primarily handle 2D data and lack effective 3D data processing capabilities, leading to limitations in integrating and processing 3D data such as 3D point clouds and depth data, resulting in accuracy loss and limited format support.
Innovation Solution
A 3D data processing pipeline that integrates with video analysis applications, allowing for the combination of depth and color frames, supporting various depth data types, and enabling scalable data sourcing, filtering, and rendering, with customizable components for user-specific algorithms and protocols, facilitating the fusion of 3D data with 2D video analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional multimedia and AI pipelines are used for 3D data processing, then 2D-based image processing and deep learning can be applied, but 3D data processing capability is limited and depth accuracy is lost
Solution Approach 1:
The patent transitions from 2D image processing to 3D point cloud processing by introducing a dedicated 3D data processing pipeline. This pipeline handles 3D data in its native three-dimensional format rather than forcing it into 2D representations, thereby preserving depth information and enabling true 3D processing capabilities while maintaining measurement precision.
2Adaptability or versatility
If depth data is merged into color frames as a fourth channel (RGBD format), then 3D data can be processed using conventional pipelines, but depth accuracy is lost due to format limitations
Solution Approach 1:
Instead of projecting 3D depth data onto a 2D plane as a fourth color channel (which loses precision), the patent creates a separate 3D processing pipeline that maintains point cloud data in its native 3D space. This allows depth values to be preserved with their full precision while still enabling integration with conventional 2D video processing pipelines when needed.
3Ease of manufacture
If conventional solutions with limited frame buffer and negotiation limitations are used, then existing 2D processing infrastructure can be leveraged, but 3D data processing is complicated and restricted
Solution Approach 1:
The patent segments the data processing system into distinct 2D and 3D processing pipelines. The 3D pipeline handles point cloud data with its own frame buffer and negotiation mechanisms, while the 2D pipeline continues to handle video frames. This segmentation allows each pipeline to be optimized for its specific data type without the limitations imposed by conventional unified pipelines, thereby improving both integration ease and 3D processing flexibility.
Data Source
AI summary
In various examples, a three-dimensional (3D) data processing pipeline for autonomous systems and applications is presented. Systems and methods are disclosed for 3D point cloud data processing fused with video analysis applications. Using the systems and methods described herein, processing of 3D data may be performed in different multimedia frameworks, allowing a user to use common libraries and/or to implement custom libraries on top of the existing system design. As a result, conventional 2D video processing may be combined with 3D data processing, to allow for data representing a flat 2D world to represent a rich 3D world. In this way, the fused 3D depth and/or range data with 2D camera image data allows for perception and/or vision that is more powerful, accurate, and precise.