IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to algorithms
Performance of optical flow techniques
International Journal of Computer Vision
Introspective sorting and selection algorithms
Software—Practice & Experience
The scientist and engineer's guide to digital signal processing
The scientist and engineer's guide to digital signal processing
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Introductory Techniques for 3-D Computer Vision
Introductory Techniques for 3-D Computer Vision
Non-parametric Local Transforms for Computing Visual Correspondence
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Layered 4D Representation and Voting for Grouping from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Disambiguating Visual Motion Through Contextual Feedback Modulation
Neural Computation
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
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Neural mechanisms for mid-level optical flow pattern detection
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Variational Multi-Valued Velocity Field Estimation for Transparent Sequences
Journal of Mathematical Imaging and Vision
Temporal prediction and spatial regularization in differential optical flow
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Multiple classifier systems for the classificatio of audio-visual emotional states
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
A hidden markov model based approach for facial expression recognition in image sequences
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
Multiple classifier systems for the recogonition of human emotions
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Motion-based prediction is sufficient to solve the aperture problem
Neural Computation
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We have previously developed a neurodynamical model of motion segregation in cortical visual area V1 and MT of the dorsal stream. The model explains how motion ambiguities caused by the motion aperture problem can be solved for coherently moving objects of arbitrary size by means of cortical mechanisms. The major bottleneck in the development of a reliable biologically inspired technical system with real-time motion analysis capabilities based on this neural model is the amount of memory necessary for the representation of neural activation in velocity space. We propose a sparse coding framework for neural motion activity patterns and suggest a means by which initial activities are detected efficiently. We realize neural mechanisms such as shunting inhibition and feedback modulation in the sparse framework to implement an efficient algorithmic version of our neural model of cortical motion segregation. We demonstrate that the algorithm behaves similarly to the original neural model and is able to extract image motion from real world image sequences. Our investigation transfers a neuroscience model of cortical motion computation to achieve technologically demanding constraints such as real-time performance and hardware implementation. In addition, the proposed biologically inspired algorithm provides a tool for modeling investigations to achieve acceptable simulation time.