Closed form solutions to image flow equations for planar surfaces in motion
Computer Vision, Graphics, and Image Processing
Computation of component image velocity from local phase information
International Journal of Computer Vision
A Three-Frame Algorithm for Estimating Two-Component Image Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion recovery from image sequences using only first order optical flow information
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
Region-based tracking using affine motion models in long image sequences
CVGIP: Image Understanding
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Dynamic updating of planar structure and motion: the case of constant motion
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive 3-D Visual Motion Estimation Using Subspace Constraints
International Journal of Computer Vision
Reducing "Structure From Motion": A General Framework for Dynamic Vision Part 1: Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense structure from a dense optical flow sequence
Computer Vision and Image Understanding
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Signal Processing: Model Based Approach
Signal Processing: Model Based Approach
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from Motion Causally Integrated Over Time
IEEE Transactions on Pattern Analysis and Machine Intelligence
Matching Widely Separated Views Based on Affine Invariant Regions
International Journal of Computer Vision
Image and Vision Computing
Visual motion and structure estimation using sliding mode observers
International Journal of Systems Science
Stereo vision based motion parameter estimation
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Occlusion boundary detection using pseudo-depth
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Adjustable linear models for optic flow based obstacle avoidance
Computer Vision and Image Understanding
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A recursive structure from motion algorithm based on optical flow measurements taken from an image sequence is described. It provides estimates of surface normals in addition to 3D motion and depth. The measurements are affine motion parameters which approximate the local flow fields associated with near-planar surface patches in the scene. These are integrated over time to give estimates of the 3D parameters using an extended Kalman filter. This also estimates the camera focal length and, so, the 3D estimates are metric. The use of parametric measurements means that the algorithm is computationally less demanding than previous optical flow approaches and the recursive filter builds in a degree of noise robustness. Results of experiments on synthetic and real image sequences demonstrate that the algorithm performs well.