Entity

Time filter

Source Type


Kurz C.,MPI Informatik Saarbrucken | Wu X.,MPI Informatik Saarbrucken | Wand M.,MPI Informatik Saarbrucken | Wand M.,University Utrecht | And 3 more authors.
Computer Graphics Forum | Year: 2014

In this paper, we propose a new method for reconstructing 3D models from a noisy and incomplete 3D scan and a coarse template model. The main idea is to maintain characteristic high-level features of the template that remain unchanged for different variants of the same type of object. As invariants, we chose the partial symmetry structure of the template model under Euclidian transformations, i.e. we maintain the algebraic structure of all reflections, rotations and translations that map the object partially to itself. We propose an optimization scheme that maintains continuous and discrete symmetry properties of this kind while registering a template against scan data using a deformable iterative closest points (ICP) framework with thin-plate-spline regularization. We apply our new deformation approach to a large number of example data sets and demonstrate that symmetry-guided template matching often yields much more plausible reconstructions than previous variants of ICP. In this paper, we propose a new method for reconstructing 3D models from a noisy and incomplete 3D scan and a coarse template model. The main idea is to maintain characteristic high-level features of the template that remain unchanged for different variants of the same type of object. As invariants, we chose the partial symmetry structure of the template model under Euclidean transformations, i.e., we maintain the algebraic structure of all reflections, rotations, and translations that map the object partially to itself. © 2014 The Authors Computer Graphics Forum © 2014 The Eurographics Association and John Wiley & Sons Ltd.


Cadik M.,MPI Informatik Saarbrucken | Cadik M.,Brno University of Technology | Herzog R.,MPI Informatik Saarbrucken | Mantiuk R.,Bangor University | And 3 more authors.
Computer Graphics Forum | Year: 2013

In this work, we present an analysis of feature descriptors for objective image quality assessment. We explore a large space of possible features including components of existing image quality metrics as well as many traditional computer vision and statistical features. Additionally, we propose new features motivated by human perception and we analyze visual saliency maps acquired using an eye tracker in our user experiments. The discriminative power of the features is assessed by means of a machine learning framework revealing the importance of each feature for image quality assessment task. Furthermore, we propose a new data-driven full-reference image quality metric which outperforms current state-of-the-art metrics. The metric was trained on subjective ground truth data combining two publicly available datasets. For the sake of completeness we create a new testing synthetic dataset including experimentally measured subjective distortion maps. Finally, using the same machine-learning framework we optimize the parameters of popular existing metrics. © 2013 The Eurographics Association and John Wiley & Sons Ltd.


Cadik M.,MPI Informatik Saarbrucken | Herzog R.,MPI Informatik Saarbrucken | Mantiuk R.,Bangor University | Myszkowski K.,MPI Informatik Saarbrucken | Seidel H.-P.,MPI Informatik Saarbrucken
ACM Transactions on Graphics | Year: 2012

Reliable detection of global illumination and rendering artifacts in the form of localized distortion maps is important for many graphics applications. Although many quality metrics have been developed for this task, they are often tuned for compression/transmission artifacts and have not been evaluated in the context of synthetic CG-images. In this work, we run two experiments where observers use a brush-painting interface to directly mark image regions with noticeable/objectionable distortions in the presence/absence of a high-quality reference image respectively. The collected data shows a relatively high correlation between the with-reference and no-reference observer markings. Also our demanding perpixel image-quality datasets reveal weaknesses of both simple (PSNR MSE sCIE-Lab) and advanced (SSIM MS-SSIM HDRVDP-2) quality metrics. The most problematic are excessive sensitivity to brightness and contrast changes the calibration for near visibility-threshold distortions lack of discrimination between plausible/implausible illumination and poor spatial localization of distortions for multi-scale metrics. We believe that our datasets have further potential in improving existing quality metrics but also in analyzing the saliency of rendering distortions and investigating visual equivalence given our with- and no-reference data. © 2012 ACM.

Discover hidden collaborations