Structure from Motion with Wide Circular Field of View Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
A unifying geometric representation for central projection systems
Computer Vision and Image Understanding - Special issue on omnidirectional vision and camera networks
Omnidirectional Vision Based Topological Navigation
International Journal of Computer Vision
Image-based Visual Servoing with Central Catadioptric Cameras
International Journal of Robotics Research
Indoor navigation of a non-holonomic mobile robot using a visual memory
Autonomous Robots
Decoupled visual servoing based on the spherical projection of points
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Visual navigation of a quadrotor aerial vehicle
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Proposition and comparison of catadioptric homography estimation methods
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Multiple homographies with omnidirectional vision for robot homing
Robotics and Autonomous Systems
Decoupled image-based visual servoing for cameras obeying the unified projection model
IEEE Transactions on Robotics
Camera Models and Fundamental Concepts Used in Geometric Computer Vision
Foundations and Trends® in Computer Graphics and Vision
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In this paper we consider the images taken from pairs ofparabolic catadioptric cameras separated by discrete motions.Despite the nonlinearity of the projection model, theepipolar geometry arising from such a system, like the perspectivecase, can be encoded in a bilinear form, the catadioptricfundamental matrix. We show that all such matriceshave equal Lorentzian singular values, and they definea nine-dimensional manifold in the space of 4 脳 4 matrices.Furthermore, this manifold can be identified with a quotientof two Lie groups. We present a method to estimate a matrixin this space, so as to obtain an estimate of the motion.We show that the estimation procedures are robust to modestdeviations from the ideal assumptions.