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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.

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Gaze tracking can be divided into two-dimensional (2-D) gaze-estimation method and three-dimensional (3-D) gazeestimation method. 3-D gaze-estimation method can simplify user calibration and track gaze under full free head movement. To solve the shortage of traditional 3-D gaze-estimation method, this paper proposes a 3-D eyeball optical axis (OA) reconstruction method for single-camera multi-source head-mounted system. The method directly calculates the vector of the OA from the pupil image on the basis of the corneal center, and then reconstructs the eyeball OA. The results of simulation experiments show the effectiveness of the method.