Registration of Translated and Rotated Images Using Finite Fourier Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
Robust Real-Time Face Detection
International Journal of Computer Vision
The Angular Difference Function and Its Application to Image Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sub-Pixel Estimation Error Cancellation on Area-Based Matching
International Journal of Computer Vision
A High-Accuracy Passive 3D Measurement System Using Phase-Based Image Matching
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
An FFT-based technique for translation, rotation, and scale-invariant image registration
IEEE Transactions on Image Processing
Deterministic edge-preserving regularization in computed imaging
IEEE Transactions on Image Processing
Extension of phase correlation to subpixel registration
IEEE Transactions on Image Processing
Pseudopolar-based estimation of large translations, rotations, and scalings in images
IEEE Transactions on Image Processing
Entropy-Controlled Quadratic Markov Measure Field Models for Efficient Image Segmentation
IEEE Transactions on Image Processing
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Motion estimation is one of the most important tasks in computer vision. One popular technique for computing dense motion fields consists in defining a large enough set of candidate motion vectors, and assigning one of such vectors to each pixel, so that a given cost function is minimized. In this work we propose a novel method for finding a small set of adequate candidates, making the minimization process computationally more efficient. Based on this method, we present algorithms for the estimation of dense optical flow using two minimization approaches: one based on a classic block-matching procedure, and another one based on entropy-controlled quadratic Markov measure fields which allow one to obtain smooth motion fields. Finally, we present the results obtained from the application of these algorithms to examples taken from the Middlebury database.