Performance of optical flow techniques
International Journal of Computer Vision
Estimating the heading direction using normal flow
International Journal of Computer Vision
Using Discriminant Eigenfeatures for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Ambiguities in Structure From Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learned Models for Estimation of Rigid and ArticulatedHuman Motion from Stationary or Moving Camera
International Journal of Computer Vision
Measuring the Affine Transform Using Gaussian Filters
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Generalized Image Matching: Statistical Learning of Physically-Based Deformations
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Accurate Dense Optical Flow Estimation Using Adaptive Structure Tensors and a Parametric Model
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Direct Estimation of Structure and Motion from Multiple Frames
Direct Estimation of Structure and Motion from Multiple Frames
Direct methods for estimation of structure and motion from three views
Direct methods for estimation of structure and motion from three views
What Can Projections of Flow Fields Tell Us About the Visual Motion
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Towards Direct Recovery of Shape and Motion Parameters from Image Sequences
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Steerable Kernels for Arbitrarily-Sampled Spaces
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Is appearance-based structure from motion viable?
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Field Testing of an Integrated Surface/Subsurface Modeling Technique for Planetary Exploration
International Journal of Robotics Research
Adjustable linear models for optic flow based obstacle avoidance
Computer Vision and Image Understanding
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A novel procedure is presented to construct image-domain filters (receptive fields) that directly recover local motion and shape parameters. These receptive fields are derived from training on image deformations that best discriminate between different shape and motion parameters. Beginning with the construction of 1-D receptive fields that detect local surface shape and motion parameters within cross sections, we show how the recovered model parameters are sufficient to produce local estimates of optical flow, focus of expansion, and time to collision. The theory is supported by a series of experiments on well-known image sequences for which ground truth is available. Comparisons against published results are quite competitive, which we believe to be significant given the local, feed-forward nature of the resulting algorithms.