Abstract
Computer-vision-based space circular target detection has a wide range of applications in visual measurement, object detection, and other fields. The space circular target is projected into an ellipse in the camera for localization. Traditional methods based on monocular vision use a precise calculation model to calculate the center coordinate and normal vector of the space circular target according to the image’s elliptic parameters. However, this accurate calculation method has the disadvantage of poor anti-interference ability in practical application. Aiming at the shortcomings of the above traditional calculation method, this paper proposes an optimization method for fitting the circular target in 3D space, where the image ellipse is projected back into 3D space and then detects the center coordinate and normal vector of the space circular target. Unlike the traditional method, this approach is not sensitive to the image’s elliptic parameters; it has stronger noise resistance performance and notable application value. The feasibility and effectiveness of the proposed method were verified by both simulation and practical experimental results.
Highlights
Three-dimensional (3D) measurement and 3D reconstruction [1,2] are important research topics in the field of computer vision
Researchers have established a 3D object detection and pose estimation based on monocular images [8], for example, where 3D object properties are first regressed using a deep convolutional neural network and combined with geometric constraints provided by a 2D object bounding box to produce a complete 3D bounding box
This paper proposes a novel space circular target detection method based on monocular vision
Summary
Three-dimensional (3D) measurement and 3D reconstruction [1,2] are important research topics in the field of computer vision. It is necessary to detect the parameters of the imaging ellipse accurately during the image segmentation stage, but various noise factors alter the pose of the elliptic projection, creating measuring errors of the normal and center coordinates of the space circular target plane. When using this method for iris detection in an eye tracking system, it is dependent on (and sensitive to) the detection of image ellipse parameters.
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