Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Robust recovery of the epipolar geometry for an uncalibrated stereo rig
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads
IEEE Transactions on Pattern Analysis and Machine Intelligence
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Contextual Inference in Contour-Based Stereo Correspondence
International Journal of Computer Vision
Differential geometric consistency extends stereo to curved surfaces
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Estimating the essential matrix by efficient linear techniques
IEEE Transactions on Circuits and Systems for Video Technology
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Stereoscopic vision is a capability that supports the ability of robots to interact with visually complex environments. Epipolar geometry captures the projective relationship between the cameras in a stereo vision system, assisting in the reconstruction of three-dimensional information. However, a basic problem arises for robots with active vision systems whose cameras move with respect to each other: the epipolar geometry changes with this motion. Such problems are especially noticeable in work with humanoid robots, whose cameras move in order to emulate human gaze behavior. We develop an epipolar kinematic model that solves this problem by building a kinematic model based on the optical properties of a stereo vision system. We show how such a model can be used in order to update the epipolar geometry for the head of a humanoid robot.