Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Intensity- and Gradient-Based Stereo Matching Using Hierarchical Gaussian Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Binocular shape reconstruction: psychological plausibility of the 8-point algorithm
Computer Vision and Image Understanding
Fast relative depth computation for an active stereo vision system
Real-Time Imaging
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
A New Correlation Criterion Based on Gradient Fields Similarity
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
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In this paper, a fast method is presented for computing the 3D Euclidean distance with a stereo head-eye system using a disparity map, a vergence angle, and a relative disparity. Our approach is to use the dense disparity for an initial vergence angle and a fixation point for its distance from a center point of two cameras. Neither camera calibration nor prior knowledge is required. The principle of the human visual system is applied to a stereo head-eye system with reasonable assumptions. Experimental results show that the 3D Euclidean distance can be easily estimated from the relative disparity and the vergence angle. The comparison of the estimated distance of objects with their real distance is given to evaluate the performance of the proposed method.