Modeling Light Reflection for Computer Color Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing Optical Flow with Physical Models of Brightness Variation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
Hierarchical Estimation and Segmentation of Dense Motion Fields
International Journal of Computer Vision
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
International Journal of Computer Vision
Constraints for the estimation of displacement vector fields from image sequences
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Robust motion estimation under varying illumination
Image and Vision Computing
Dynamic Texture Detection Based on Motion Analysis
International Journal of Computer Vision
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Unification of Multichannel Motion Feature Using Boolean Polynomial
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Approximation-free running SVD and its application to motion detection
Pattern Recognition Letters
Visual navigation of mobile robot using optical flow and visual potential field
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Illumination-robust variational optical flow using cross-correlation
Computer Vision and Image Understanding
A color neuromorphic approach for motion estimation
WMVC'09 Proceedings of the 2009 international conference on Motion and video computing
International Journal of Computer Vision
A hybrid color distance for image segmentation
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
A cognitive approach for robots' vision using unsupervised learning and visual saliency
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Illumination-robust dense optical flow using census signatures
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
Dense versus Sparse Approaches for Estimating the Fundamental Matrix
International Journal of Computer Vision
On improving the robustness of variational optical flow against illumination changes
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream
Human automatic detection and tracking for outdoor video
Integrated Computer-Aided Engineering
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Since years variational methods belong to the most accurate techniques for computing the optical flow in image sequences. However, if based on the grey value constancy assumption only, such techniques are not robust enough to cope with typical illumination changes in real-world data. In our paper we tackle this problem in two ways: First we discuss different photometric invariants for the design of illumination-robust variational optical flow methods. These invariants are based on colour information and include such concepts as spherical/ conical transforms, normalisation strategies and the differentiation of logarithms. Secondly, we embed them into a suitable multichannel generalisation of the highly accurate variational optical flow technique of Brox et al. This in turn allows us to access the true potential of such invariants for estimating the optical flow. Experiments with synthetic and real-world data demonstrate the success of combining accuracy and robustness: Even under strongly varying illumination, reliable and precise results are obtained.