Sky Region Filtering in Mobile Platform Environment Detection
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Solution Overview
Problem
Existing environment detection technologies, such as stereo vision systems, face challenges in accurately determining depth information for interfering features like the sky, due to lack of texture and frequent lighting changes, which can lead to inaccurate navigation and obstacle detection.
Innovation Solution
A computer-implemented method that uses a color vision sensor to identify regions in an image and filters out non-sky regions using non-image data from an inertial measurement unit, determining the sky regions based on color information and performing environment detection while excluding interfering sky features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stereo vision systems are used to detect depth information, then depth measurement capability is provided, but accuracy deteriorates for interfering features like the sky due to lack of texture and frequent lighting changes
Solution Approach 1:
The patent extracts and removes the sky region from the image data used for depth calculation. By identifying the sky as an interfering feature and excluding it from the set of regions used for stereo vision processing, the system prevents the sky's lack of texture and lighting changes from degrading depth measurement accuracy.
Solution Approach 2:
The patent segments the image into multiple regions and processes each region differently. By dividing the image and identifying which regions correspond to the sky versus useful features, the system can apply appropriate processing to each segment, maintaining depth accuracy for relevant features while ignoring the sky.
2Productivity
If all regions in the image are used for environment detection, then detection coverage is maximized, but computational efficiency deteriorates due to unnecessary operations on interfering features
Solution Approach 1:
The patent extracts and removes the sky region from the image data used for depth calculation. By identifying the sky as an interfering feature and excluding it from the set of regions used for stereo vision processing, the system prevents the sky's lack of texture and lighting changes from degrading depth measurement accuracy.
Solution Approach 2:
The patent performs preliminary identification and classification of regions before main processing. By pre-identifying which regions are sky (interfering features) and excluding them from further processing, the system avoids unnecessary computational operations on those regions, improving overall processing efficiency.
3Measurement precision
If color information is used to identify sky regions, then sky detection accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent transforms color information into a simplified representation (e.g., average color, color histogram) of each region. By changing the parameter representation from raw pixel data to summarized color characteristics, the system achieves accurate sky identification while reducing processing complexity.
Data Source
AI summary
Identifying interfering features in the detection of an environment adjacent to a mobile platform, and associated systems and methods are disclosed herein. A representative method can include identifying candidate regions from a color image obtained by a color vision sensor carried by a mobile platform, filtering out a first region subset of regions based, at least in part, on non-image data obtained by a second sensor carried by the mobile platform, determining a second subset of regions as corresponding to an interfering feature based, at least in part, on color information, and performing environment detection based, at least in part, on the second subset of regions. Furthermore, the method can comprise transforming data corresponding to the subset of regions to integrate with non-color environment data obtained from another sensor carried by the mobile platform.