Abstract-The aim of this work is to study several strategies for the preservation of flow discontinuities in variational optical flow methods. We analyze the combination of robust functionals and diffusion tensors in the smoothness assumption. Our study includes the use of tensors based on decreasing functions, which has shown to provide good results. However, it presents several limitations and usually does not perform better than other basic approaches. It typically introduces instabilities in the computed motion fields in the form of independent blobs of vectors with large magnitude.We propose two alternatives to overcome these drawbacks: first, a simple approach that combines the decreasing function with a minimum isotropic smoothing; second, a method that looks for the best parameter configuration that preserves the important motion contours and avoid instabilities. It relies on the input images and the regularization parameter. It is fully automatic, providing a near-optimal value for many sequences, as shown in the experiments. Both proposals allow to detect the contours of the motion field and produce more stable solutions for a large range of parameters. In the experimental results, we present a detailed study and comparison of the different strategies.

In this work, we describe an implementation of the variational method proposed by Brox et al. in 2004, which yields accurate optical flows with low running times. It has several benefits with respect to the method of Horn and Schunck: it is more robust to the presence of outliers, produces piecewise-smooth flow fields and can cope with constant brightness changes. This method relies on the brightness and gradient constancy assumptions, using the information of the image intensities and the image gradients to find correspondences. It also generalizes the use of continuous L 1 functionals, which help mitigate the effect of outliers and create a Total Variation (TV) regularization. Additionally, it introduces a simple temporal regularization scheme that enforces a continuous temporal coherence of the flow fields. Source CodeThe source code, the code documentation, and the online demo are accessible at the IPOL web page of this article 1 . In this page an implementation is available for download. This file contains two directories: one for the spatial method and another for the temporal method. The spatial method is suitable for general image sequences, while the temporal method should be used when the flow fields are known to be very continuous.

In this work, we present an implementation and thorough study of the Harris corner detector. This feature detector relies on the analysis of the eigenvalues of the autocorrelation matrix. The algorithm comprises seven steps, including several measures for the classification of corners, a generic non-maximum suppression method for selecting interest points, and the possibility to obtain the corners position with subpixel accuracy. We study each step in detail and propose several alternatives for improving the precision and speed. The experiments analyze the repeatability rate of the detector using different types of transformations. Source Code The reviewed source code and documentation for this algorithm are available from the web page of this article 1. Compilation and usage instruction are included in the README.txt file of the archive.

In this work, we present an implementation of discontinuity-preserving strategies in TV-L 1 optical flow methods. These are based on exponential functions that mitigate the regularization at image edges, which usually provide precise flow boundaries. Nevertheless, if the smoothing is not well controlled, it may produce instabilities in the computed motion fields. We present an algorithm that allows three regularization strategies: the first one uses an exponential function together with a TV process; the second one combines this strategy with a small constant that ensures a minimum isotropic smoothing; the third one is a fully automatic approach that adapts the diffusion depending on the histogram of the image gradients. The last two alternatives are aimed at reducing the effect of instabilities. In the experiments, we observe that the pure exponential function is highly unstable while the other strategies preserve accurate motion contours for a large range of parameters. Source CodeThe source code, its documentation and the online demo are accessible at the IPOL web page of this article 1 . In this page an implementation is available for download.

No abstract

The automatic synthesis of abstract textures is, to some extent, feasible. As evidenced by abstract art theoreticians, one can think of an abstract picture as a tree of elementary shapes interacting according to a short list of compositional laws such as occlusion, exclusion and bordering, and by rendering rules such as transparency, tessellation and color selection. Randomizing the shape generator and the composition and rendering laws yields an algorithm generating random abstract textures. We have designed a user-friendly online tool that implements this algorithm.

We propose four algorithms for computing the inverse optical flow between two images. We assume that the forward optical flow has already been obtained and we need to estimate the flow in the backward direction. The forward and backward flows can be related through a warping formula, which allows us to propose very efficient algorithms. These are presented in increasing order of complexity. The proposed methods provide high accuracy with low memory requirements and low running times. In general, the processing reduces to one or two image passes. Typically, when objects move in a sequence, some regions may appear or disappear. Finding the inverse flows in these situations is difficult and, in some cases, it is not possible to obtain a correct solution. Our algorithms deal with occlusions very easy and reliably. On the other hand, disocclusions have to be overcome as a post-processing step. We propose three approaches for filling disocclusions. In the experimental results, we use standard synthetic sequences to study the performance of the proposed methods, and show that they yield very accurate solutions. We also analyze the performance of the filling strategies.

Abstract. We identified design problems related to the architecture, ergonomy, and performance in the previous version of the Image Processing on Line (IPOL) demonstration system. In order to correct them we moved to an architecture of microservices and performed many refactorings. This article first describes the state of the art in Reproducible Research platforms and explains IPOL in that context. The specific problems which were found are discussed, along with the solutions implemented in the new demo system, and the changes in its architecture with respect to the previous system. Finally, we expose the challenges of the system in the short term.