Closed form solutions to image flow equations for planar surfaces in motion
Computer Vision, Graphics, and Image Processing
Structure and motion from optical flow under orthographic projection
Computer Vision, Graphics, and Image Processing
Interpretation of Image Flow: A Spatio-Temporal Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bounds on time-to-collision and rotational component from first-order derivatives of image flow
Computer Vision, Graphics, and Image Processing
Surface shape from the deformation of apparent contours
International Journal of Computer Vision
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
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Image divergence and deformation from closed curves
International Journal of Robotics Research
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
International Journal of Computer Vision
Parameterized modeling and recognition of activities
Computer Vision and Image Understanding
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
The Accuracy of the Computation of Optical Flow and of the Recovery of Motion Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive Estimation of 3D Motion and Surface Structure from Local Affine Flow Parameters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Time-to-Collision Estimation from Motion Based on Primate Visual Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards direct recovery of shape and motion parameters from image sequences
Computer Vision and Image Understanding
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision
A Fast Joint Bioinspired Algorithm for Optic Flow and Two-Dimensional Disparity Estimation
ICVS '09 Proceedings of the 7th International Conference on Computer Vision Systems: Computer Vision Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review and evaluation of methods estimating ego-motion
Computer Vision and Image Understanding
Fly-inspired visual steering of an ultralight indoor aircraft
IEEE Transactions on Robotics
Vision-based active safety system for automatic stopping
Expert Systems with Applications: An International Journal
Autonomous Pedestrian Collision Avoidance Using a Fuzzy Steering Controller
IEEE Transactions on Intelligent Transportation Systems
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An original framework to recover the first-order spatial description of the optic flow is proposed. The approach is based on recursive filtering, and uses a set of linear models that dynamically adjust their properties on the basis of context information. These models are inspired by the experimental evidence about motion analysis in biological systems. By checking the presence of these models in the optic flow through a multiple model Kalman Filter, it is possible to compute the coefficients of the affine description and to use this information for estimating the motion of the observer as well as the three-dimensional orientation of the surfaces in some points of interest in the scene. In order to systematically validate the approach, a set of benchmarking sequences is used, and, finally, the proposed algorithm is successfully applied in real-world automotive situations.