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IPOL Preprints — Latest public preprints from IPOL.Extraction of the Level Lines of a Bilinear ImagePascal Monassehttp://www.ipol.im/pub/pre/269/
http://www.ipol.im/pub/pre/269/
Sat, 29 Jun 2019 16:00:24 +02002019-06-29T14:03:29ZWe detail precisely an algorithm for the extraction of the level lines of a bilinear image, which is a continuous function interpolating bilinearly a discrete image. If we discard the levels of the discrete image, where topological difficulties arise, a level line is a concatenation of branches of hyperbolas. The algorithm tracks these branches and provides a sampling of the level lines in the form of closed polygons. If the level line contains a saddle point, the hyperbola degenerates to orthogonal segments, where an arbitrary but consistent choice is adopted for the tracking at the bifurcation. In any case, the extracted polygons are disjoint and enclose a bounded region. This allows to order the level lines in an enclosure tree hierarchy, which may be used for a variety of filters. Recovering this tree is a simple post-processing of the extraction algorithm.A Data Set for the Study of Human Locomotion with Inertial Measurements UnitsCharles Truong,
Rémi Barrois-Müller,
Thomas Moreau,
Clément Provost,
Aliénor Vienne-Jumeau,
Albane Moreau,
Pierre-Paul Vidal,
Nicolas Vayatis,
Stéphane Buffat,
Alain Yelnik,
Damien Ricard,
Laurent Oudrehttp://www.ipol.im/pub/pre/265/
http://www.ipol.im/pub/pre/265/
Sun, 23 Jun 2019 18:31:36 +02002019-06-23T16:31:36ZThis article thoroughly describes a data set of 1020 multivariate gait signals collected with two inertial measurement units, from 230 subjects undergoing a fixed protocol: standing still, walking 10 m, turning around, walking back and stopping. In total, 8.5 h of gait time series are distributed. The measured population was composed of healthy subjects as well as patients with neurological or orthopedic disorders. An outstanding feature of this data set is the amount of signal metadata that are provided. In particular, the start and end time stamps of more than 40,000 footsteps are available, as well as a number of contextual information about each trial. This exact data set was used in Oudre, et al. (2018) to design and evaluate a step detection procedure.A Parallel, O (n) Algorithm for an Unbiased, Thin WatershedThéodore Chabardès,
Petr Dokládal,
Matthieu Faessel,
Michel Bilodeauhttp://www.ipol.im/pub/pre/215/
http://www.ipol.im/pub/pre/215/
Thu, 09 May 2019 12:30:32 +02002019-05-09T10:30:32ZThe watershed transform is a powerful tool for morphological segmentation. Most common
implementations of this method involve a strict hierarchy on gray tones in processing the pixels
composing an image. This hierarchical dependency complexifies the efficient use of modern
computational architectures. This paper introduces a new way of computing the watershed
transform that alleviates the sequential nature of hierarchical queue propagation. It is shown
that this method can directly relate to the hierarchical flooding. Simultaneous and disorderly
growth can now be used to maximize performances on modern architectures. Higher speed is
reached, bigger data volume can be processed. Experimental results show increased performances
regarding execution speed and memory consumption.An Implementation of the Mean Shift AlgorithmDamir Demirovićhttp://www.ipol.im/pub/pre/255/
http://www.ipol.im/pub/pre/255/
Thu, 09 May 2019 12:23:49 +02002019-05-09T10:23:49ZIn this paper we present an implementation and analysis of Mean shift algorithm in C++
language. Mean shift is a general non-parametric mode finding/clustering procedure widely
used in image processing and analysis and computer vision techniques such as image denosing,
image segmentation, motion tracking etc.WatervoxelsPierre Cettour-Janet,
Clément Cazorla,
Vaia Machairas,
Quentin Delannoy,
Nathalie Bednarek,
François Rousseau,
Etienne Décencière,
Nicolas Passathttp://www.ipol.im/pub/pre/250/
http://www.ipol.im/pub/pre/250/
Thu, 09 May 2019 12:14:40 +02002019-05-31T07:49:18ZIn this article, we present the n-dimensional version of the waterpixels, namely the
watervoxels. Waterpixels constitute a simple, yet efficient alternative to standard superpixel paradigms,
initially developed in the field of computer vision for reducing the space cost of input images
without altering the accuracy of further image processing / analysis procedures. Waterpixels
were initially proposed in a 2-dimensional version. Their extension to 3-dimensions—and more
generally n-dimensions—is however possible, in particular in the Cartesian grid. Indeed, water-
pixels mainly rely on a seeded watershed transformation applied on a saliency map defined as
the linear combination of a gradient map and a distance map. We propose a description of the
algorithmics of watervoxels in n-dimensional Cartesian grids. We also discuss its parameters
and its time cost. A source code for 2- and 3-dimensional versions of watervoxels is provided,
such as a 2-dimensional demonstrator. This article can be seen as the companion of the article
“Waterpixels”, published in 2015 in IEEE Transactions on Image Processing.An Analysis and Implementation of Natural Image Enhancement MethodDang Thanh Trung,
Shaohua Chenr,
Azeddine Beghdadi,
Nguyen thi Quynh Hoahttp://www.ipol.im/pub/pre/252/
http://www.ipol.im/pub/pre/252/
Sat, 16 Mar 2019 22:56:11 +01002019-03-16T21:56:11ZDigital image enhancement is to improve the appearance of images to human viewers. This is one of extremely difficult issues in image processing. The NECI algorithm (Natural Enhancement of Color Image) is a robust and effective approach for color image enhancement. The core of this algorithm is Retinex model, a simulation model of human color vision. A fully framework for enhancement process is composed of four main steps: global tone mapping, Retinex-based local contrast enhancement, histogram rescaling, and texture enhancement.
The experimental results on different types of natural images show that the proposed algorithm not only preserves the ambience of image but also avoid side effects such as light condition changes, color temperature alteration, or additional artifacts, etc which lead to unnaturally sharpened images or dramatic white balance changes. In the output color images, no additional light sources are added to the scene, or no halo effect and blocking effect are amplified due to over-enhancement. Moreover, all parameters are image-dependent so that the process requires no parameter tuning.Comparison of Optical Flow Methods under Stereomatching with Short BaselinesTristan Dagobert,
Nelson Monzón,
Javier Sánchezhttp://www.ipol.im/pub/pre/217/
http://www.ipol.im/pub/pre/217/
Mon, 16 Oct 2017 14:24:59 +02002019-01-21T12:49:29ZThis article studies the effectiveness of optical flow methods applied to short
baseline image pairs under different noise levels. New metrics have been
developed to analyze the results because the usual metrics are inadequate in a
subpixel context. We have used the implementation of some standard optical flow
methods adapted to the stereo problem. Our experiments show that the Brox
et al. method produces the least errors, with a 60% success rate and a
relative precision at 1/100th of a pixel. On the other hand, our comparison
shows that a discontinuity preserving method, derived from Brox et al.,
also provides competitive results at the same time that it yields disparities
with more details and correct contours.Joint Large-Scale Motion Estimation and Image ReconstructionHendrik Dirkshttp://www.ipol.im/pub/pre/193/
http://www.ipol.im/pub/pre/193/
Thu, 24 Nov 2016 14:13:55 +01002018-07-22T11:40:36ZThis article describes the implementation of the joint motion estimation and image reconstruction framework presented by Burger, Dirks and Schönlieb and extends this framework to large-scale motion between consecutive image frames. The variational framework uses displacements between consecutive frames based on the optical
flow approach to improve the image reconstruction quality on the one hand and the motion estimation quality on the other. The energy functional consists of a
data-fidelity term with a general operator that connects the input sequence to the solution, it has a total variation term for the image sequence and is connected to the underlying flow using an optical flow term. Additional spatial regularity for the flow is modeled by a total variation regularizer for both components of the flow. The numerical minimization is performed in an alternating manner using
primal-dual techniques. The resulting schemes are presented as pseudo-code together with a short numerical evaluation.Joint TV-L1 Optical Flow and Occlusion EstimationJuan Francisco Garamendi Bragado,
Coloma Ballester,
Lluís Garrido,
Vanel Lazcano,
Vicent Caselleshttp://www.ipol.im/pub/pre/118/
http://www.ipol.im/pub/pre/118/
Thu, 05 Feb 2015 13:37:40 +01002018-07-22T11:40:36ZThis document describes an implementation of the energy functional minimization proposed by Ballester, Garrido, Lazcano and Caselles for joint optical flow and occlusion estimation. The method is based on the TV-L1 approach introduced Zach, Pock and Bischof in 2007 but with the particularity of detecting occlusions. The energy functional is composed by a regularization term (over the optical flow and the occlusion fields) using the total variation, a data term using the L1 norm, and a term, which is based on the divergence of the flow, for dealing with the occlusions.