Vehicle Feature Detection with State-Switched Cameras
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Solution Overview
Problem
Existing vehicle-mounted camera systems struggle to detect features when obstacles, such as parked vehicles, cover the detection target, leading to incomplete feature representation in generated images.
Innovation Solution
A feature detection system utilizing multiple cameras on a vehicle, including a panoramic camera, to capture different areas, with one camera capturing a larger area during travel and another capturing a closer area during parking, and employing viewpoint transformation to generate aerial images for accurate feature detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single camera is used to capture images during vehicle travel, then the device complexity is reduced, but the feature detection reliability deteriorates when obstacles cover the detection target
Solution Approach 1:
The patent divides the imaging task into two segments: a first camera captures images during vehicle travel, while a second camera captures images when the vehicle is parked. This segmentation allows each camera to operate in its optimal scenario, improving overall feature detection reliability without requiring both cameras to operate simultaneously, thus managing device complexity.
Solution Approach 2:
The patent implements dynamic camera selection based on vehicle state. The system determines whether the vehicle is traveling or parked and automatically switches between using the first camera or the second camera accordingly. This dynamic adaptation ensures reliable feature detection across different operational conditions while optimizing the use of available camera resources.
2Area of stationary object
If a first camera captures a large area during travel, then the coverage area is improved, but the detection precision deteriorates when features are obscured by obstacles
Solution Approach 1:
The patent segments the imaging function between two cameras: the first camera provides wide-area coverage during travel, while the second camera provides close-up, high-precision imaging when the vehicle is parked. This segmentation allows the system to achieve both large coverage area and high detection precision by using the appropriate camera for each scenario.
Solution Approach 2:
The patent introduces a vehicle state determination mechanism as an intermediary that decides which camera to use based on whether the vehicle is traveling or parked. This intermediary ensures that the system selects the appropriate imaging approach to achieve both wide coverage and precise feature detection as needed.
3Measurement precision
If a second camera captures a closer area when parked, then the feature detection precision is improved, but the productivity deteriorates due to additional processing requirements
Solution Approach 1:
The patent implements dynamic camera selection that activates the second camera only when the vehicle is parked and high-precision feature detection is needed. During normal travel, the system uses the first camera, avoiding unnecessary processing overhead. This dynamic approach maintains high detection precision when required while preserving overall system productivity.
Solution Approach 2:
The patent applies different imaging qualities to different operational contexts: the first camera provides sufficient-quality images during travel, while the second camera provides high-precision images only when the vehicle is parked. This local quality differentiation ensures high detection precision is achieved only where necessary, avoiding the productivity penalty of always using high-precision imaging.
4Reliability
If viewpoint transformation is applied to generate aerial images, then the feature detection capability is improved, but the computational complexity increases
Solution Approach 1:
The patent applies viewpoint transformation dynamically only when the vehicle is parked and the second camera is used, rather than continuously during all operations. This dynamic application improves feature detection capability when needed while minimizing the computational complexity overhead by avoiding unnecessary transformations during normal travel.
Data Source
AI summary
A feature detection device includes a processor configured to determine whether a vehicle is parked, based on at least one of the speed, steering angle, and shifter position of the vehicle; detect one or more predetermined features from a first image representing a first area around the vehicle in a section of road in which the vehicle is traveling, the first image being generated by a first camera provided on the vehicle, and detect the one or more predetermined features from a second image representing a second area closer to the vehicle than the first area in a section of road in which the vehicle is parked, the second image being generated by a second camera provided on the vehicle.