Robot vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Bilateral filtering-based optical flow estimation with occlusion detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Variational optical flow computation in real time
IEEE Transactions on Image Processing
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Due to the limitation of the gradient constraint, only the normal flow, which is one of the optical flow components that is in the direction of the image gradient, can be computed directly. Consequently, an additional smoothness assumption has to be imposed in order to compute the optical flow. However, such assumption could yield a mismatch, especially on the boundaries of moving objects, besides the computational complexity issue. To address these concerns, in this paper, a three-dimensional (3-D) gradient constraint is developed and imposed for computing the optical flow without exploiting any smoothness assumption on the motion field. Based on this 3-D gradient constraint, the tangent flow, which is another optical flow component that is perpendicular to the normal flow, could be obtained through our derived closed-form solution at each pixel position. This also means that the standard aperture problem could be efficiently solved. The experimental results show that the proposed approach yields a fairly precise optical flow field with a very low computational load.