Use all functions optimally: LOGIN NOW

    Painterly Rendering using Limited Paint Color Palettes (Unknown language)

    In: Vision, Modeling and Visualization ; 135-145  ; 2018

    How to get this title?

    Check access
    Download
    Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
    Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

    Export, share and cite

    We present a painterly rendering method for digital painting systems as well as visual feedback based painting machines that automatically extracts color palettes from images and computes mixture recipes for these from a set of real base paint colors based on the Kubelka-Munk theory. In addition, we present a new algorithm for distributing stroke candidates, which creates paintings with sharp details and contrasts. Our system is able to predict dry compositing of thinned or thick paint colors using an evaluation scheme based on example data collected from a calibration step and optical blending. We show results generated using a software stroke-based renderer and a painting machine.

    Table of contents conference proceedings

    The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

    1
    A Fast and Efficient Semi-guided Algorithm for Flat Coloring Line-arts
    Fourey, Sébastien / Tschumperlé, David / Revoy, David et al. | 2018
    11
    Interactive Interpolation of Metallic Effect Car Paints
    Golla, Tim / Klein, Reinhard et al. | 2018
    21
    Dynamic Environment Mapping for Augmented Reality Applications on Mobile Devices
    Monroy, Rafael / Hudon, Matis / Smolic, Aljosa et al. | 2018
    29
    WithTeeth: Denture Preview in Augmented Reality
    Amirkhanov, Aleksandr / Amirkhanov, Artem / Bernhard, Matthias / Toth, Zsolt / Stiller, Sabine / Geier, Andreas / Gröller, Eduard / Mistelbauer, Gabriel et al. | 2018
    39
    The Parallel Eigenvectors Operator
    Oster, Timo / Rössl, Christian / Theisel, Holger et al. | 2018
    47
    Automatic Generation of Saliency-based Areas of Interest for the Visualization and Analysis of Eye-tracking Data
    Fuhl, Wolfgang / Kuebler, Thomas / Santini, Thiago / Kasneci, Enkelejda et al. | 2018
    55
    Automatic Infant Face Verification via Convolutional Neural Networks
    Wöhler, Leslie / Zhang, Hangjian / Albuquerque, Georgia / Magnor, Marcus et al. | 2018
    63
    Parameter Space Comparison of Inertial Particle Models
    Holbein, Jérôme / Günther, Tobias et al. | 2018
    71
    Efficient Global Registration for Nominal/Actual Comparisons
    Berkei, Sarah / Limper, Max / Hörr, Christian / Kuijper, Arjan et al. | 2018
    79
    Hierarchical Additive Poisson Disk Sampling
    Dieckmann, Alexander / Klein, Reinhard et al. | 2018
    89
    Fast and Dynamic Construction of Bounding Volume Hierarchies Based on Loose Octrees
    Gu, Feng / Jendersie, Johannes / Grosch, Thorsten et al. | 2018
    97
    Compressed Bounding Volume Hierarchies for Efficient Ray Tracing of Disperse Hair
    Martinek, Magdalena / Stamminger, Marc / Binder, Nikolaus / Keller, Alexander et al. | 2018
    103
    Efficient Subsurface Scattering Simulation for Time-of-Flight Sensors
    Bulczak, David / Kolb, Andreas et al. | 2018
    111
    Identifying Similar Eye Movement Patterns with t-SNE
    Burch, Michael et al. | 2018
    119
    Correlated Point Sampling for Geospatial Scalar Field Visualization
    Roveri, Riccardo / Lehmann, Dirk J. / Gross, Markus / Günther, Tobias et al. | 2018
    127
    Clustering for Stacked Edge Splatting
    Abdelaal, Moataz / Hlawatsch, Marcel / Burch, Michael / Weiskopf, Daniel et al. | 2018
    135
    Painterly Rendering using Limited Paint Color Palettes
    Lindemeier, Thomas / Gülzow, J. Marvin / Deussen, Oliver et al. | 2018
    147
    Web-based Volume Rendering using Progressive Importance-based Data Transfer
    Mwalongo, Finian / Krone, Michael / Reina, Guido / Ertl, Thomas et al. | 2018
    155
    Interactive Visual Exploration of Line Clusters
    Kanzler, Mathias / Westermann, Rüdiger et al. | 2018

    How to get this title?

    Check access
    Download
    Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
    Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

    Export, share and cite

    Feedback