Publications in the field of Motion Estimation:



  Scene Flow Estimation from Light Fields via the Preconditioned Primal-Dual Algorithm paper              
  Stefan Heber, Thomas Pock       GCPR 2014  
paper In this paper we present a novel variational model to jointly estimate geometry and motion from a sequence of light fields captured with a plenoptic camera. The proposed model uses the so-called sub-aperture representation of the light field. Sub-aperture images represent images with slightly different viewpoints, which can be extracted from the light field. The sub-aperture representation allows us to formulate a convex global energy functional, which enforces multi-view geometry consistency, ...
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  Non-Local Total Generalized Variation for Optical Flow Estimation paper              
  Rene Ranftl, Kristian Bredies, Thomas Pock       European Conference on Computer Vision 2014  
paper In this paper we introduce a novel higher-order regularization term. The proposed regularizer is a non-local extension of the popular second-order Total Generalized variation, which favors piecewise affine solutions and allows to incorporate soft-segmentation cues into the regularization term. These properties make this regularizer especially appealing for optical flow estimation, where it offers accurately localized motion boundaries and allows to resolve ambiguities in the matching term.
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  An iterated l1 Algorithm for Non-smooth Non-convex Optimization in Computer Vision paper              
  Peter Ochs, Alexey Dosovitskiy, Thomas Brox, Thomas Pock       CVPR 2013  
paper Natural image statistics indicate that we should use non-convex norms for most regularization tasks in image processing and computer vision. Still, they are rarely used in practice due to the challenge to optimize them. Recently, iteratively reweighed l1 minimization has been proposed as a way to tackle a class of non-convex functions by solving a sequence of convex l2 - l1 problems. Here we extend the problem class to linearly constrained optimization of a Lipschitz continuous function, which is the sum of a convex function and a function being concave and increasing on the non-negative orthant (possibly non-convex and non-concave on the whole space).
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  Convex Approaches for High Performance Video Processing paper              
  Manuel Werlberger       Phd Thesis 2012  
paper Accurate and robust motion estimation in image sequences is essential for high quality video processing and digital film restoration. The ability to deal with strong outliers and large impaired regions is especially important for restoring historical film. Typical artifacts like brightness changes, noise, scratches or other forms of missing data may cause the algorithms to fail. Even in situations without disturbance and only changing illuminationsthe algorithms often have problems to compute the correct motion.
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  Joint Motion Estimation and Segmentation of Complex Scenes with Label Costs and Occlusion Modeling paper              
  Markus Unger, Manuel Werlberger, Thomas Pock, Horst Bischof       CVPR 2012, Providence, Rhode Island  
paper We propose a unified variational formulation for joint motion estimation and segmentation with explicit occlusion handling. This is done by a multi-label representation of the flow field, where each label corresponds to a parametric representation of the motion. We use a convex formulation of the multi-label Potts model with label costs and show that the asymmetric map-uniqueness criterion can be integrated into our formulation by means of convex constraints.
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  Optical Flow Guided TV-L1 Video Interpolation and Restoration paper              
  Manuel Werlberger, Thomas Pock, Markus Unger, Horst Bischof       EMMCVPR 2011, Saint Petersburg, Russia  
paper The ability to generate intermediate frames between two given images in a video sequence is an essential task for video restoration and video post-processing. In addition, restoration requires robust denoising algorithms, must handle corrupted frames and recover from impaired frames accordingly.
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  Motion Estimation with Non-Local Total Variation Regularization paper           links  
  Manuel Werlberger, Thomas Pock, Horst Bischof       CVPR 2010, San Francisco, CA  
paper State-of-the-art motion estimation algorithms suffer from three major problems: Poorly textured regions, occlusions and small scale image structures. Based on the Gestalt principles of grouping we propose to incorporate a low level image segmentation process in order to tackle these problems. Our new motion estimation algorithm is based on non-local total variation regularization...
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  FlowGames paper   videos          
  Jakob Santner, Manuel Werlberger, Thomas Mauthner, Wolfgang Paier, Horst Bischof       1st Int. Workshop on Computer Vision for Computer Games (CVCG) in conjunction with IEEE CVPR 2010  
paper Computer vision-based interfaces to games hold the promise of rich natural interaction and thus a more realistic gaming experience. Therefore, the video games industry started to develop and market computer vision-based games recently with great success. Due to limited computational resources, they employ mostly simple algorithms such as background subtraction, instead of sophisticated motion estimation or gesture recognition methods...
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  PROST: Parallel Robust Online Simple Tracking paper           links  
  Jakob Santner, Christian Leistner, Amir Saffari, Thomas Pock, Horst Bischof       CVPR 2010, San Francisco, CA  
paper Tracking-by-detection is increasingly popular in order to tackle the visual tracking problem. Existing adaptive methods suffer from the drifting problem, since they rely on self-updates of an on-line learning method. In contrast to previous work that tackled this problem by employing semi-supervised or multiple-instance learning, we show that augmenting an on-line learning method with complementary tracking approaches can lead to more stable results...
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  Local, Semi-global, and Global Optimization for Motion Estimation paper              
  Werner Trobin       Phd Thesis 2009  
paper Motion cues are an integral part of our visual experience, and therefore it is not surprising that the recovery of motion information from image sequences is a prominent problem in computer vision...
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  Advanced Data Terms for Variational Optic Flow Estimation paper              
  Frank Steinbruecker, Thomas Pock, Daniel Cremers       Vision, Modeling, and Visualization Workshop, Braunschweig (GER)  
paper In this paper, we present optic flow algorithms which are based on a variety of increasingly sophisticated data terms. Such data terms allow to better identify correspondences between points in either image than the traditional intensity difference since they characterize the local image structure more uniquely. We present an algorithmic framework which allows to directly incorporate arbitrary data terms...
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  Tracking as Segmentation of Spatial-Temporal Volumes by Anisotropic Weighted TV paper              
  Markus Unger, Thomas Mauthner, Thomas Pock, Horst Bischof       EMMCVPR 2009  
paper Tracking is usually interpreted as finding an object in single consecutive frames. Regularization is done by enforcing temporal smoothness of appearance, shape and motion. We propose a tracker, by interpreting the task of tracking as segmentation of a volume in 3D...
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  Anisotropic Huber-L1 Optical Flow paper           links  
  Manuel Werlberger, Werner Trobin, Thomas Pock, Andreas Wedel, Daniel Cremers, Horst Bischof       British Machine Vision Conference 2009  
paper The presented work is motivated by the problem of restoring severely degraded historic video material via an optical flow-based interpolation. In order to increase the robustness as well as the accuracy of discontinuity preserving variational optical flow models, we propose two extensions...
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  Flowball 2009 - An Interactive Game based on Optical Flow paper              
  Wolfgang Paier       Bachelor Thesis  
paper This document roughly covers the steps which are needed to provide a user interface solely based on optical flow. We used two di fferent digital cameras: A simple webcam or an expensive AVT-Marlin industrial camera. We also used two different algorithms to calculate the optical flow...
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  Video Super Resolution using Duality Based TV-L1 Optical Flow paper              
  Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers       DAGM 2009  
paper In this paper, we propose a variational framework for computing a superresolved image of a scene from an arbitrary input video. To this end, we employ a recently proposed quadratic relaxation scheme for high accuracy optic flow estimation. Subsequently we estimate a high resolution image using a variational approach...
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  Large Displacement Optical Flow Computation without Warping paper              
  Frank Steinbruecker, Thomas Pock, Daniel Cremers       International Conference on Computer Vision 2009  
paper We propose an algorithm for large displacement optical flow estimation which does not require the commonly used coarse-to-fine warping strategy. It is based on a quadratic relaxation of the optical flow functional which decouples data term and regularizer...
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  Structure- and Motion-adaptive Regularization for High Accuracy Optic Flow paper              
  Andreas Wedel, Daniel Cremers, Thomas Pock, Horst Bischof       International Conference on Computer Vision 2009  
paper The accurate estimation of motion in image sequences is of central importance to numerous computer vision applications. Most competitive algorithms compute flow fields by minimizing an energy made of a data and a regularity term. To date, the best performing methods rely on rather simple purely geometric regularizers favoring smooth motion. In this paper, we revisit regularization and show that appropriate adaptive regularization substantially improves the accuracy of estimated motion fields. In particular, we systematically evaluate regularizers which adaptively favor rigid body motion (if supported by the image data) and motion field discontinuities that coincide with discontinuities of the image structure. The proposed algorithm relies on sequential convex optimization, is real-time capable and outperforms all previously published algorithms by more than one average rank on the Middlebury optic flow benchmark.
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  Duality TV-L1 Flow with Fundamental Matrix Prior paper              
  Andreas Wedel, Thomas Pock, Juergen Braun, Uwe Franke, Daniel Cremers       Image and Vision Computing, Auckland (NZ), 2008  
paper Variational techniques yield the most accurate results for dense optical flow fields between two images. They have the nice property of inherent smoothness to cope with untextured image regions: the filling-in of such regions is driven by neighbouring pixels. Such filling-in is not always the best choice...
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  Continuous Energy Minimization via Repeated Binary Fusion paper              
  Werner Trobin, Thomas Pock, Daniel Cremers, Horst Bischof       European Conference on Computer Vision 2008  
paper Variational problems, which are commonly used to solve lowlevel vision tasks, are typically minimized via a local, iterative optimization strategy, e.g. gradient descent. Since every iteration is restricted to a small, local improvement, the overall convergence can be slow...
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paper Flowball is an interactive game presented at our Institute's annualy Open Lab Night in October 2008. Using dense optical flow computed in realtime on a Geforce GTX 280, flowball is a demonstration of current capabilities of GPGPU for the interested public.
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  Automatic Differentiation for GPU-Accelerated 2D/3D Registration paper              
  Markus Grabner, Thomas Pock, Tobias Gross, Bernhard Kainz       Proc. 5th International Conference on Automatic Differentiation  
paper We demonstrate the applicability of automatic differentiation (AD) techniques to a class of 2D/3D registration problems which are highly computationally intensive and can therefore greatly benefit from a parallel implementation on recent graphics processing units (GPUs)...
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  An Unbiased Second-Order Prior for High-Accuracy Motion Estimation paper              
  Werner Trobin, Thomas Pock, Daniel Cremers, Horst Bischof       DAGM 2008  
paper Virtually all variational methods for motion estimation regularize the gradient of the flow field, which introduces a bias towards piecewise constant motions in weakly textured areas. We propose a novel regularization approach...
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  Fast Total Variation for Computer Vision paper              
  Thomas Pock       Phd Thesis 2008  
paper Motivated by statistical inference methods, variational methods are among the most successful methods to solve a number of different Computer Vision problems. Variational methods aim to minimize an energy functional...
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  A Duality Based Approach for Realtime TV-L1 Optical Flow paper              
  Christopher Zach, Thomas Pock, Horst Bischof       DAGM 2007  
paper Energy-based methods are highly successful and accurate approaches to calculate the optical flow between images. If discontinuity preservation and robustness against image noise and local illumination changes are required...
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