Bird Detection via Image Motion Analysis
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Solution Overview
Problem
Existing bird detection methods require mechanisms to calculate distance, increasing costs and face misjudgment between birds and airplanes, and particle image velocimetry methods lack clear detection processes.
Innovation Solution
A bird detection system that extracts bird candidate images from captured images and determines bird presence based on the time required for these images to move within the image, eliminating the need for distance calculation and improving differentiation between birds and airplanes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a mechanism for detecting distance (such as stereo camera or distance calculation program) is used to calculate the speed of flying objects, then the speed detection accuracy is improved, but the equipment cost increases
Solution Approach 1:
The patent extracts and eliminates the distance detection mechanism from the bird detection system. Instead of using stereo cameras or distance calculation programs, the invention uses a single camera that captures images and detects birds based on image processing and motion analysis alone, thereby removing the costly distance measurement component while maintaining detection functionality
Solution Approach 2:
The patent replaces the mechanical/optical distance measurement system (stereo camera) with an image processing-based detection system. By substituting physical distance measurement mechanisms with computational image analysis methods, the system achieves bird detection without requiring complex hardware for depth sensing
2Productivity
If particle image velocimetry or optical flow method is used to detect birds by calculating velocity vectors, then the detection capability is improved, but the system complexity and computational requirements increase
Solution Approach 1:
The patent employs simpler, computationally less intensive image processing methods compared to particle image velocimetry or optical flow. By using more straightforward image analysis techniques that require less computational power and system complexity, the invention achieves practical bird detection without the overhead of complex velocity field calculations
Solution Approach 2:
The patent extracts and removes the complex velocity vector calculation processes from the detection system. Instead of implementing particle image velocimetry or optical flow methods that require sophisticated computational frameworks, the invention uses simplified image processing approaches that directly analyze image data without computing complex velocity fields
3Measurement precision
If the optical flow method is used to calculate velocity vectors at individual position coordinates, then the speed calculation precision is improved, but the processing time and computational load increase
Solution Approach 1:
The patent applies partial action by focusing image processing efforts only on relevant regions of the captured images rather than analyzing the entire image frame. By concentrating computational resources on areas where birds are likely to appear or where motion is detected, the system achieves efficient processing without requiring exhaustive analysis of all image coordinates
Solution Approach 2:
The patent uses simpler, faster image processing algorithms that provide sufficient detection accuracy without the computational overhead of optical flow methods. By employing more efficient processing techniques that require less computational power and time, the system achieves practical bird detection with reduced processing delays
Data Source
AI summary
A bird detection device equipped with: a captured image acquisition unit that acquires a captured image; a bird candidate image extraction unit that extracts a bird candidate image, which is a candidate bird image, from the captured image; and a bird detection determination unit that, on the basis of the time required for the bird candidate image to move in accordance with the size of the bird candidate image in the captured image, determines whether a bird has been detected. The bird detection determination unit also can determine whether a bird has been detected on the basis of the degree of change in the shape of the bird candidate image for a prescribed time interval.