Camera Optical Flow Speed Estimation Without Radar
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Solution Overview
Problem
Existing methods for estimating the relative speed of objects with respect to a vehicle rely heavily on radars, which may fail or have limited coverage, necessitating an alternative method for obtaining this critical information.
Innovation Solution
A computer-implemented method using optical flow analysis from camera images to calculate relative speed between an object and a camera, based on parameters such as expansion and translation, allowing for the estimation of speed without radar data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radar is used to determine relative speed, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the radar-based relative speed measurement system with a camera-based optical flow analysis system. The camera captures image sequences, and optical flow algorithms compute pixel displacement between frames to estimate object motion. This substitution eliminates the need for complex radar hardware while providing comparable relative speed information through computational methods.
Solution Approach 2:
The patent employs standard camera sensors, which are significantly cheaper and more widely available than radar systems. The camera hardware is commoditized and can be integrated into vehicles at lower cost, making the relative speed estimation system more accessible and economically viable despite the computational processing required.
2Measurement precision
If radar is used to detect objects, then measurement precision is improved, but reliability worsens when radar fails or coverage is limited
Solution Approach 1:
The patent makes the camera system multi-functional by enabling it to perform both object detection/tracking and relative speed estimation through optical flow analysis. This single sensor platform can serve multiple purposes: identifying objects in the scene, tracking their positions across frames, and calculating their motion vectors. This universality improves reliability by eliminating single points of failure associated with separate radar and camera systems.
Solution Approach 2:
The patent introduces optical flow computation as an intermediary process that bridges the gap between simple image capture and complex relative speed measurement. The optical flow algorithm acts as a mediator that extracts motion information from image sequences, translating visual data into quantitative speed estimates without requiring direct radar measurements.
3Device complexity
If optical flow analysis is used instead of radar, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent employs dynamic optical flow computation that adapts to varying scene conditions. The system processes image sequences in real-time, continuously updating motion estimates as objects move and scene conditions change. This dynamic approach allows the system to maintain measurement precision despite the simpler camera-based hardware by adapting computational parameters to current scene dynamics.
Solution Approach 2:
The patent implements feedback mechanisms where the optical flow results are continuously refined based on tracking performance and motion consistency checks. The system uses feedback from multiple image frames and motion vector coherence to correct and improve speed estimates, compensating for the inherently lower precision of camera-based measurements compared to radar through iterative refinement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides accurate relative speed information using common camera sensors, enabling effective object tracking and vehicle control even when radar data is unavailable, with high stability and accuracy in estimating motion parameters.
Implementation Method 1
image frames outputted by one or more cameras
Implementation Method 2
determining a value of an optical flow between the initial image and the final image, the optical flow defining, for pixels of the initial image, an estimated motion thereof
Data Source
AI summary
A computer-implemented method for calculating information relative to a relative speed between an objectand a camera, based on two images of the object acquired by the camera. The method comprises:determining a value of an optical flowbetween the two images and, altogether with or after the determination of the value the optical flow, determining at least one parameter of the transformation, using the optical flow; andcalculating information relative to a relative speed between the object and the camera, based on said at least one parameter of the transformation.