Polyline Construction from Line Segments for Localization
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Solution Overview
Problem
Traditional computer vision systems face challenges in constructing coherent models of detected objects from broken line segments, which can lead to increased processing time and reduced localization accuracy in applications like autonomous driving, due to the segmented representation of continuous edges.
Innovation Solution
A method is introduced to construct a polyline representation from line segments by selecting candidate segments and merging neighboring segments based on proximity and distance criteria, thereby forming continuous edges for improved edge modeling and localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If broken line segments are used to represent continuous edges, then object detection can be performed, but localization accuracy deteriorates and processing time increases
Solution Approach 1:
The patent merges multiple broken line segments into a single continuous polyline representation by identifying spatial and angular relationships between segments. This combining process reduces the number of discrete objects to process, thereby decreasing processing time while improving localization accuracy through a unified edge representation.
Solution Approach 2:
The patent segments the polyline representation into individual line segments for detection, then reconstructs them into a continuous polyline. This segmentation approach allows the system to work with manageable discrete elements while achieving continuous edge representation, resolving the contradiction between detectability and accuracy.
2Difficulty of detecting and measuring
If broken line segments are used to represent continuous edges, then edge detection can be performed, but the representation coherence deteriorates
Solution Approach 1:
The patent combines multiple broken line segments into a unified polyline structure that maintains spatial relationships and angular continuity. This merging preserves the detectability of individual segments while creating a coherent continuous representation, thereby improving representation coherence without losing edge detection capability.
3Reliability
If multiple broken line segments are processed individually, then detection completeness is maintained, but processing complexity increases
Solution Approach 1:
The patent merges multiple line segments into a single polyline object that retains information about all constituent segments. This approach maintains detection completeness by preserving all segment data while reducing processing complexity through unified object management, eliminating the need to process each segment independently.
Data Source
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AI summary
An approach is provided for generating a polyline from line segments (e.g., line segments representing objects detected by a computer vision system). The approach involves selecting a line segment from a plurality of line segments. The approach also involves determining a neighboring line segment from among the plurality of line segments. The determined neighboring line segment has a closest distance to the line segment from among the plurality of line segments. The approach further involves merging the line segment and the neighboring line segment into a polyline based on determining that the closest distance is a mutual closest distance between line segment and the neighboring line segment.