3D Background Detection Using Ray Peaks and Catchment Regions
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Solution Overview
Problem
Conventional background detection techniques for 3D object detection systems are inaccurate, inefficient, and require excessive computational and memory resources, making them unsuitable for embedded systems.
Innovation Solution
A method and system that divide the 3D space into rays with defined peaks and catchment regions to determine background points, using minimal computational resources and adaptive to changing environments, allowing for accurate and real-time background detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional background detection techniques are used, then detection accuracy may be improved, but computational resources and memory usage increase excessively
Solution Approach 1:
The patent segments the 3D space into multiple rays extending from the sensor, with each ray independently processed. Peaks are defined along each ray to represent background structures, and catchment regions are assigned to each peak. This segmentation allows the system to process background detection in smaller, manageable units along each ray rather than processing all points in the entire point cloud simultaneously, significantly reducing computational resources while maintaining detection accuracy.
2Measurement precision
If conventional background detection techniques are used, then detection accuracy may be improved, but processing speed decreases
Solution Approach 1:
The patent performs preliminary actions by defining peaks and catchment regions along each ray before processing data points. The peaks represent expected background structures, and their catchment regions pre-establish the areas where background points are likely to be found. This preliminary structuring allows for faster classification of data points during actual processing, as each point can be quickly assigned to the nearest peak's catchment region without complex computations, thereby improving processing speed while maintaining accuracy.
3Measurement precision
If conventional background detection techniques are used, then detection accuracy may be improved, but memory usage increases excessively
Solution Approach 1:
The patent extracts only the essential background information by identifying and storing peak locations and their catchment region parameters along each ray, rather than storing complete background models for the entire 3D space. This extraction approach focuses memory resources on storing only the critical peak definitions and catchment region boundaries, significantly reducing memory usage while preserving the ability to accurately classify background points during processing.
4Measurement precision
If high-resolution background detection is implemented, then detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by treating each ray independently with its own set of peaks and catchment regions, allowing the system to achieve high-resolution background detection locally along each ray while keeping the overall computational complexity manageable. The complexity is distributed across multiple independent ray processing units rather than requiring a single complex global processing system, enabling high accuracy without proportionally increasing overall device complexity.
Data Source
AI summary
A method for determining a background in 3D space includes: receiving, via a sensor, a plurality of data points for the 3D space; dividing the 3D space into a plurality of rays extending from the sensor; defining a plurality of peaks for each ray; and defining a catchment region for each peak for each ray. Each data point is enclosed by a corresponding ray. Each peak is located at a peak distance from the sensor and comprises a peak height. The catchment region for each peak includes a catchment distance from the corresponding peak towards and away from the sensor. For each data point from the plurality of data points, the method includes: determining the corresponding ray enclosing the data point; determining a containing peak for which the data point lies within the catchment region; and incrementing the peak height of the containing peak by a peak increment value.