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检索条件"任意字段=4th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2013"

共 84 条记录，以下是31-40 订阅

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Wimmelbild analysis with approximate curvature coding distance images

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Bergbauer, Julia Tari, Sibel TU Munich Garching bei Muenchen DE-85747 Germany Middle East Technical University Ankara TR-06800 Turkey

ISBN: (纸本)9783642382666

We consider a task of tracing out target figures hidden in teeming figure pictures come to known as Wimmelbild(er). Wimmelbild is a popular genre of visual puzzles;a timeless classic for children, artists and cognitive scientists. Particularly suited to the considered task, we propose a diffuse representation which serves as a heuristic approximation mimicking curvature coding distance images. Curvature coding distance images received increased attention in recent years. Typically, they are computed as solutions to variants of Poisson PDE. the proposed approximation is based on erosion of the white space (background) followed by isotropic averaging, hence, does not require solving a PDE. © 2013 Springer-Verlag.

关键词： Numerical methods

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Multi scale shape index for 3D object recognition

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Bonde, Ujwal Badrinarayanan, Vijay Cipolla, Roberto Deparment of Engineering University of Cambridge Cambridge United Kingdom

ISBN: (纸本)9783642382666

We present Multi scale Shape Index (MSSI), a novel feature for 3D object recognition. Inspired by the scale space filtering theory and Shape Index measure proposed by Koenderink & Van Doorn [6], this feature associates different forms of shape, such as umbilics, saddle regions, parabolic regions to a real valued index. this association is useful for representing an object based on its constituent shape forms. We derive closed form scale space equations which computes a characteristic scale at each 3D point in a point cloud without an explicit mesh structure. this characteristic scale is then used to estimate the Shape Index. We quantitatively evaluate the robustness and repeatability of the MSSI feature for varying object scales and changing point cloud density. We also quantify the performance of MSSI for object category recognition on a publicly available dataset. © 2013 Springer-Verlag.

关键词： Object recognition

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Spatio-Temporal scale Selection in Video Data 6th

Spatio-Temporal Scale Selection in Video Data

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6th international conference on scale space and variational methods in computer vision (ssvm)

作者： Lindeberg, Tony KTH Royal Inst Technol Computat Brain Sci Lab Dept Computat Sci & Technol Sch Comp Sci & Commun Stockholm Sweden

ISBN: (纸本)9783319587714;9783319587707

We present a theory and a method for simultaneous detection of local spatial and temporal scales in video data. the underlying idea is that if we process video data by spatio-temporal receptive fields at multiple spatial and temporal scales, we would like to generate hypotheses about the spatial extent and the temporal duration of the underlying spatio-temporal image structures that gave rise to the feature responses. For two types of spatio-temporal scale-space representations, (i) a non-causal Gaussian spatio-temporal scale space for offline analysis of pre-recorded video sequences and (ii) a time-causal and time-recursive spatio-temporal scale space for online analysis of real-time video streams, we express sufficient conditions for spatio-temporal feature detectors in terms of spatio-temporal receptive fields to deliver scale covariant and scale invariant feature responses. A theoretical analysis is given of the scale selection properties of six types of spatio-temporal interest point detectors, showing that five of them allow for provable scale covariance and scale invariance. then, we describe a time-causal and time-recursive algorithm for detecting sparse spatio-temporal interest points from video streams and show that it leads to intuitively reasonable results.

关键词： Temporal scale Video Data Local Extremum scale Covariance scale Selection these keywords were added by machine and not by the authors. this process is experimental and the keywords may be updated as the learning algorithm improves.

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Layered mean shift methods

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Šurkala, Milan Mozdřeň, Karel Fusek, Radovan Sojka, Eduard Technical University of Ostrava Faculty of Electrical Engieneering and Informatics 17. listopadu 15 708 33 Ostrava-Poruba Czech Republic

ISBN: (纸本)9783642382666

Segmentation is one of the most discussed problems in image processing. Many various methods for image segmentation exist. the mean-shift method is one of them and it was widely developed in recent years and it is still being developed. In this paper, we propose a new method called Layered Mean Shift that uses multiple mean-shift segmentations with different bandwidths stacked for elimination of the over-segmentation problem and finding the most appropriate segment boundaries. this method effectively reduces the need for the use of large kernels in the mean-shift method. therefore, it also significantly reduces the computational complexity. © 2013 Springer-Verlag.

关键词： Image segmentation

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A Cortical-Inspired Model for Orientation-Dependent Contrast Perception: A Link with Wilson-Cowan Equations 7th

A Cortical-Inspired Model for Orientation-Dependent Contrast...

引用

7th international conference on scale space and variational methods in computer vision (ssvm)

作者： Bertalmio, Marcelo Calatroni, Luca Franceschi, Valentina Franceschiello, Benedetta Prandi, Dario Univ Pompeu Fabra DTIC Barcelona Spain Ecole Polytech CNRS CMAP Palaiseau France Univ Paris Sud IMO Orsay France Fdn Asile Aveugles Lausanne Switzerland Lab Invest Neurophysiol Lausanne Switzerland Cent Supelec CNRS L2S Gif Sur Yvette France

ISBN: (纸本)9783030223687;9783030223670

We consider a differential model describing neuro-physiological contrast perception phenomena induced by surrounding orientations. the mathematical formulation relies on a cortical-inspired modelling [11] largely used over the last years to describe neuron interactions in the primary visual cortex (V1) and applied to several image processing problems [14,15,21]. Our model connects to Wilson-Cowan-type equations [26] and it is analogous to the one used in [3,4,16] to describe assimilation and contrast phenomena, the main novelty being its explicit dependence on local image orientation. To confirm the validity of the model, we report some numerical tests showing its ability to explain orientation-dependent phenomena (such as grating induction) and geometric-optical illusions [18,24] classically explained only by filtering-based techniques [7,20].

关键词： Orientation-dependent modelling Wilson-Cowan equations Primary visual cortex Contrast perception variational modelling

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Solving the uncalibrated photometric stereo problem using total variation

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Quéau, Yvain Lauze, François Durou, Jean-Denis IRIT UMR CNRS 5505 Toulouse France Dept. of Computer Science Univ. of Copenhagen Denmark

ISBN: (纸本)9783642382666

In this paper we propose a new method to solve the problem of uncalibrated photometric stereo, making very weak assumptions on the properties of the scene to be reconstructed. Our goal is to solve the generalized bas-relief ambiguity (GBR) by performing a total variation regularization of both the estimated normal field and albedo. Unlike most of the previous attempts to solve this ambiguity, our approach does not rely on any prior information about the shape or the albedo, apart from its piecewise smoothness. We test our method on real images and obtain results comparable to the state-of-the-art algorithms. © 2013 Springer-Verlag.

关键词： Photometry

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Why is the census transform good for robust optic flow computation?

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hafner, David Demetz, Oliver Weickert, Joachim Mathematical Image Analysis Group Faculty of Mathematics and Computer Science Saarland University 66041 Saarbrücken Germany

ISBN: (纸本)9783642382666

the census transform is becoming increasingly popular in the context of optic flow computation in image sequences. Since it is invariant under monotonically increasing grey value transformations, it forms the basis of an illumination-robust constancy assumption. However, its underlying mathematical concepts have not been studied so far. the goal of our paper is to provide this missing theoretical foundation. We study the continuous limit of the inherently discrete census transform and embed it into a variational setting. Our analysis shows two surprising results: the census-based technique enforces matchings of extrema, and it induces an anisotropy in the data term by acting along level lines. Last but not least, we establish links to the widely-used gradient constancy assumption and present experiments that confirm our findings. © 2013 Springer-Verlag.

关键词： Anisotropy

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Partial optimality via iterative pruning for the potts model

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Swoboda, Paul Savchynskyy, Bogdan Kappes, Jörg Schnörr, Christoph Image and Pattern Analysis Group University of Heidelberg Germany Heidelberg Collaboratory for Image Processing University of Heidelberg Germany

ISBN: (纸本)9783642382666

We propose a novel method to obtain a part of an optimal non-relaxed integral solution for energy minimization problems with Potts interactions, known also as the minimal partition problem. the method empirically outperforms previous approaches likeMQPBO and Kovtun's method in most of our test instances and especially in hard ones. As a starting point our approach uses the solution of a commonly accepted convex relaxation of the problem. this solution is then iteratively pruned until our criterion for partial optimality is satisfied. Due to its generality our method can employ any solver for the considered relaxed problem. © 2013 Springer-Verlag.

关键词： Iterative methods

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Compression of depth maps with segment-based homogeneous diffusion

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hoffmann, Sebastian Mainberger, Markus Weickert, Joachim Puhl, Michael Faculty of Mathematics and Computer Science Campus E1.7 Saarland University 66041 Saarbrücken Germany

ISBN: (纸本)9783642382666

the efficient compression of depth maps is becoming more and more important. We present a novel codec specifically suited for this task. In the encoding step we segment the image and extract between-pixel contours. Subsequently we optimise the grey values at carefully selected mask points, including both hexagonal grid locations as well as freely chosen points. We use a chain code to store the contours. For the decoding we apply a segment-based homogeneous diffusion inpainting. the segmentation allows parallel processing of the individual segments. Experiments show that our compression algorithm outperforms comparable methods such as JPEG or JPEG2000, while being competitive with HEVC (High Efficiency Video Coding). © 2013 Springer-Verlag.

关键词： Image compression

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Defect classification on specular surfaces using wavelets

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4th international conference on scale space and variational methods in computer vision, ssvm 2013

作者： Hahn, Andreas Ziebarth, Mathias Heizmann, Michael Rieder, Andreas Karlsruhe Institute of Technology Institute for Applied and Numerical Mathematics Kaiserstr. 89-93 76133 Karlsruhe Germany Karlsruhe Institute of Technology Institute for Anthropomatics Adenauerring 4 76131 Karlsruhe Germany Fraunhofer Institute of Optronics System Technologies and Image Exploitation Fraunhoferstr. 1 76131 Karlsruhe Germany

ISBN: (纸本)9783642382666

In many practical problems wavelet theory offers methods to handle data in different scales. It is highly adaptable to represent data in a compact and sparse way without loss of information. We present an approach to find and classify defects on specular surfaces using pointwise extracted features in scale space. Our results confirm the presumption that the stationary wavelet transform is better suited to localize surface defects than the classical decimated transform. the classification is based on a support vector machine (SVM) and furthermore applicable to empirically evaluate given wavelets for specific classification tasks and can therefore be used as quality measure. © 2013 Springer-Verlag.

关键词： Wavelet transforms

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