3-D structure from visual motion: modeling, representation and observability
Automatica (Journal of IFAC)
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Relative position sensing by fusing monocular vision and inertial rate sensors
Relative position sensing by fusing monocular vision and inertial rate sensors
Brief Applying the EKF to stochastic differential equations with level effects
Automatica (Journal of IFAC)
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Three-dimensional structure information can be estimated from two-dimensional perspective images using recursive estimation methods. This paper investigates possibilities to improve structure filter performance for a certain class of stochastic perspective systems by utilizing mutual information, in particular when each observed point on a rigid object is affectd by the same process noise. After presenting the dynamic system of interest, the method is applied, using an extended Kalman filter for the estimation, to a simulated time-varying multiple point vision system. The performance of a connected filter is compared, using Monte Carlo methods, to that of a set of independent filters. The idea is then further illustrated and analyzed by means of a simple linear system. Finally more formal stochastic differential equation aspects, especially the impact of transformations in the Itô sense, are discussed and related to physically realistic noise models in vision systems.