Bi-directional Feature Projection for 3D Perception Systems
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Solution Overview
Problem
3D perception models face challenges in generating comprehensive views of environments, often resulting in sparse outputs, false-positive detections, and poor resolution, particularly when transforming 2D data into 3D.
Innovation Solution
The implementation of bi-directional feature projection techniques, combining forward and backward projection methods to enhance the quality of Bird's-Eye View (BEV) representations by mapping 2D image features into 3D space and back, filling in sparse areas, and refining features based on depth consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional 3D perception models transform 2D data into 3D data using standard projection techniques, then the system can generate BEV representations, but the outputs become sparse with poor resolution and contain false-positive detections
Solution Approach 1:
The patent applies backward projection to map 3D points back to 2D image planes, allowing refinement of BEV features by checking consistency with original 2D images. This inversion process fills in sparse areas and removes false-positive detections by verifying whether projected features actually correspond to valid 2D image content.
Solution Approach 2:
The system uses the backward projection results as feedback to refine the BEV representation. By comparing the backward-projected features with the original 2D image features, the system can iteratively improve the accuracy and density of the 3D perception output, eliminating false positives and enhancing resolution in sparse regions.
2Productivity
If forward projection is used to map 2D image features to 3D space, then BEV features can be generated, but blank spaces and sparse regions appear in the output
Solution Approach 1:
Backward projection maps 3D points to 2D images, allowing the system to identify and fill sparse regions in the BEV representation by projecting back to the source 2D images where features can be recovered and re-projected to fill in the blanks.
Solution Approach 2:
The patent combines forward projection (2D to 3D) and backward projection (3D to 2D) into a unified bi-directional projection system. This merging of both projection directions allows the system to leverage information from both transformations to generate dense, complete BEV features without blank spaces.
Data Source
AI summary
In various examples, bi-directional projection techniques may be used to generate enhanced Bird's-Eye View (BEV) representations. For example, a system(s) may generate one or more BEV features associated with a BEV of an environment using a projection process that associates 2D image features to one or more first locations of a 3D space. At least partially using the BEV feature(s), the system(s) may determine one or more second locations of the 3D space that correspond to one or more regions of interest in the environment. The system(s) may then generate one or more additional BEV features corresponding to the second location(s) using a different projection process that associates the second location(s) from the 3D space to at least a portion of the 2D image features. The system(s) may then generate an updated BEV of the environment based at least on the BEV feature(s) and/or the additional BEV feature(s).