Fisheye Person Detection via Bounding Box Validation
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Solution Overview
Problem
The existing methods for detecting people using fisheye camera images face challenges such as increased processing costs and delays due to preprocessing, and a risk of false detection caused by image distortion, leading to reduced accuracy, especially in environments like building and factory automation.
Innovation Solution
A person detection system that analyzes fisheye images without preprocessing, using a human body detector and a false detection determining unit to compare the shape and size of detected bounding boxes with pre-stored references to determine valid detections, thereby eliminating false positives and improving processing speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the fisheye image is developed in a plane to eliminate distortion, then the detection accuracy is improved, but the processing cost increases and real-time detection becomes difficult
Solution Approach 1:
The patent extracts only the essential geometric characteristics (aspect ratio and area of bounding boxes) needed for validation, rather than performing complete plane development. This selective extraction maintains detection accuracy while significantly reducing processing complexity and enabling real-time detection.
Solution Approach 2:
The patent pre-calculates and stores reference values for bounding box aspect ratios and areas corresponding to different positions in the fisheye image. This preliminary action allows rapid validation during detection without performing computationally expensive plane development in real-time.
2Measurement precision
If the fisheye image is developed in a plane to eliminate distortion, then the detection accuracy is improved, but the processing cost increases
Solution Approach 1:
The patent extracts only the essential geometric characteristics (aspect ratio and area of bounding boxes) needed for validation, rather than performing complete plane development. This selective extraction maintains detection accuracy while significantly reducing processing complexity and enabling real-time detection.
Solution Approach 2:
The patent uses simple geometric comparisons (aspect ratio and area checks) instead of complex plane development algorithms. These simple validation operations are computationally inexpensive and can be performed rapidly, replacing the need for expensive preprocessing.
3Productivity
If the fisheye image is processed without plane development, then the processing speed is improved, but the detection accuracy deteriorates due to false detection
Solution Approach 1:
The patent pre-calculates and stores reference values for bounding box aspect ratios and areas corresponding to different positions in the fisheye image. This preliminary action allows rapid validation during detection without performing computationally expensive plane development in real-time.
Solution Approach 2:
The patent uses the detected bounding box characteristics (aspect ratio and area) to validate whether a detected object is a true person or false detection by comparing against reference values. This feedback mechanism maintains high detection accuracy even without plane development.
4Productivity
If the fisheye image is processed without plane development, then the processing speed is improved, but the detection accuracy deteriorates due to false detection
Solution Approach 1:
The patent pre-calculates and stores reference values for bounding box aspect ratios and areas corresponding to different positions in the fisheye image. This preliminary action allows rapid validation during detection without performing computationally expensive plane development in real-time.
Solution Approach 2:
The patent uses the detected bounding box characteristics (aspect ratio and area) to validate whether a detected object is a true person or false detection by comparing against reference values. This feedback mechanism maintains high detection accuracy even without plane development.
Data Source
AI summary
A person detection device configured to analyze a fisheye image obtained by a fisheye camera installed above a to-be-detected area to detect a person existing in the to-be-detected area includes a human body detector configured to detect a human body candidate from a fisheye image and output, as a detection result, a bounding box indicating a region on the fisheye image of each human body candidate detected, a reference storage configured to prestore a reference for a shape and/or size of the bounding box for each position or area on the fisheye image, and a false detection determining unit configured to compare the shape and/or size of the bounding box of the human body candidate contained in the detection result with the reference corresponding to a position where the human body candidate is detected to determine whether the human body candidate results from false detection.