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Oblasti výskumu

Computer vision is a science discipline with an ultimate goal to perceive, to interpret and to understand the natural images or other type of visual data.
The research in the field of computer vision is focused mainly on:

  • Medical image processing : CT and MRI radiological data processing, detection of anatomical anomalies, segmentation and 3D image registration.
  • Prediction of visual human attention: development of model of human visual attention, generation of visual saliency map.
  • Visual object detection and object recognition: development of novel methods of object detection and object recognition using 2D and 3D visual data.
In the area of information visualisation are the key research topics:
novel interaction techniques in visualization, data visualization in virtual reality and augmented reality.
Research task in computer graphics are mainly photorealistic visualization, real-time rendering, light-field capture and manipulation.

Medical Imaging, Object Detection and Object Recognition in 2D / 3D, Visual Attention Prediction, Augmented and Virtual Reality Applications, Big Data Visualization

Vanda Benešová
Associate Professor
Peter Kapec
Her research interest is focused at the fields of computer vision, image processing, signal processing and human-computer interaction.
Research interest lies at information and big data visualization, software visualization, graph visualization, visual analytics, novel interaction techniques in visualization, data visualization in virtual reality and augmented reality, source code analysis, software metrics and software representation via graph structures.

Peter Drahoš
Mainly focuses on topics related to computer graphics such as photorealistic visualization, real-time rendering, light-field capture and manipulation. Additional interests include virtual reality applications focusing on user interaction and presence as well as parallel processing.

Selected recent publications

  1. FOGELTON, Andrej - BENEŠOVÁ, Wanda
    Eye blink detection based on motion vectors analysis.
    Computer Vision and Image Understanding, 0, pp. 1–11. 2016.

  2. ILČÍKOVÁ, Ivana - BENEŠOVÁ, Wanda – POLEC, Jaroslav – CSÓKA, Tibor
    Texture aware image error concealment with fuzzy segmentation.
    Systems, Signals and Image Processing (IWSSIP), 2016 International Conference on. IEEE. 2016

  3. OLEŠOVÁ, V. - BENEŠOVÁ, Wanda - POLATSEK, Patrik
    Visual Attention in Egocentric Field-of-view using RGB-D Data.
    9th International Conference on Machine Vision. Nice: SPIE. 2016.

  4. POLATSEK, Patrik - BENEŠOVÁ, Vanda - PALETTA, Lucas - PERKO, R.
    Novelty-based Spatiotemporal Saliency Detection for Prediction of Gaze in Egocentric Video.
    IEEE Signal Processing Letters, 23(3), pp. 394–398. 2016.

  5. POLEC, Jaroslav - BENEŠOVÁ, Wanda - VARGIC, Radoslav - ILČÍKOVÁ, Ivana - CSÓKA, Tibor
    Texture Feature Extraction using an Orthogonal Transform of Arbitrarily Shaped Image Regions.
    Journal of Electronic Imaging, 25(6), 2016.

  6. TAMAJKA, Martin - BENEŠOVÁ, Vanda
    Automatic Brain Segmentation Method based on Super-voxels.
    International Conference on Systems, Signals and Image Processing IWSSIP 2016, Bratislava: IEEE. pp. 16–19, 2016.

  7. JAKAB, Marek - BENEŠOVÁ, Vanda - RAČEV, Marek
    3D Object Recognition based on Local Descriptors.
    IS&T/SPIE Electronic Imaging 2015. San Francisco, USA: SPIE. 2015

  8. MARTIN-GUTIERREZ, Jorge - FABIANI, Pena - BENEŠOVÁ, Vanda - MENESES, Dolores Maria - MORA, Carlos E.
    Augmented Reality to Promote Collaborative and Autonomous Learning in Higher Education.
    Computers in Human Behavior, 51, pp.752–761, 2015.

  9. POLATSEK, Patrik - BENEŠOVÁ, Vanda
    Bottom-up Saliency Model Generation using Superpixels.
    Proceedings of the 31st Spring Conference on Computer Graphics. ACM New York, NY, pp. 121–129, 2015.

  10. UHLÍKOVÁ, Ivana - BENEŠOVÁ, Vanda - POLEC, Jaroslav - CSÓKA, Tibor
    Texture Aware Image Error Concealment.
    EUROCON 2015. Salamanca, Spain: IEEE Catalog Number: CFP15EUR-CDR. 2015

  11. BENEŠOVÁ, Vanda - KOTTMAN, Michal
    Fast Superpixel Segmentation Using Morphological Processing.
    Proceedinks of the International Conference on Machine Vision and Machine Learning - MVML 2014. Avestia Publishing.

  12. ŠIKUDOVÁ, Elena - ČERNEKOVÁ, Zuzana - BENEŠOVÁ, Vanda - HALADOVÁ, Zuzana - KUČEROVÁ, Júlia
    Počítačové videnie Detekcia a rozpoznávanie objektov. Praha: Wikina, Praha. 2013.
    Retrieved from

  13. BENEŠOVÁ, Vanda - KOTTMAN, Michal - SIDLA, Oliver
    Hazardous Sign Detection for Safety Applications in Traffic Monitoring.
    Röning Juha & Casasent David P. (Eds.), Proceedings of SPIE, Intelligent Robots and Computer Vision XXIX: Algorithms and Techniques, Volume 8301. San Francisco, USA. 2012.

  14. SIDLA, Oliver - KOTTMAN, Michal - BENEŠOVÁ, Vanda
    Real-time Pose Invariant Logo and Pattern Detection.
    Proceedings of SPIE, Vol. 7878, p. 8, 2011
    Retrieved from pose invariant logo and pattern detection.pdf

  15. SIDLA, Oliver - BRÄNDLE, Norbert - BENEŠOVÁ, Vanda - ROSNER, Marcin - LYPETSKYY, Yuriy
    Embedded Vision Challenges.
    A. N. Belbachir (Ed.), Smart Cameras. Boston, MA: Springer US. pp. 99–117, 2010.

  16. SIDLA, Oliver - BRAENDLE, Norbert - BENEŠOVÁ, Vanda
    Towards Complex Visual Surveillance Algorithms on Smart Cameras
    Computer Vision Workshops (ICCV Workshops), 2009 IEEE 12th International Conference on Computer Vision. Kyoto: IEEE, 2009, pp. 847–853. Print ISBN: 978-1-4244-4442-7.

    Visual Analysis of Software Systems
    INES 2015 : 19th International conference on intelligent engineering systems. Bratislava, Slovakia. September 3-5, 2015. Danvers : IEEE, 2015, pp. 31-37, 2015.

  18. KAPEC, Peter - DRAHOŠ, Peter - ŠPERKA, Martin
    Trends in Information Visualization for Software Analysis and Development.
    Current Issues of Science and Research in the Global World: Proceedings of the International Conference on Current Issues of Science and Research in the Global World, Vienna, Austria; 27–28 May 2014. CRC Press, 2014. APA

  19. KAPEC, Peter - PAPRČKA, Michal - PAŽITNAJ, Adam - POLÁK, Vladimír
    Exploring 3D GPU-accelerated graph visualization with time-traveling virtual camera.
    JTACS - Journal of Theoretical and Applied Computer Science, Vol. 7, No. 2, pp 16-30, ISSN 2299-2634 (printed), 2300-5653 (online), 2013.

  20. GRZNÁR, Filip - KAPEC, Peter
    Visualizing Dynamics of Object Oriented Programs with Time Context.
    Proceedings of the 29th Spring Conference on Computer Graphics, pp. 65-72. ACM, 2013.

Important recent research results and research projects

  • KEGA 068UK-4/2011 Integrácia štúdia spracovania vizuálnej informácie a vytvorenie komplexných multimediálnych učebných materiálov.
  • VEGA:1/0625/14 Visual object class recognition in video sequences using a linkage of information derived by a semantic local segmentation and a global segmentation of visual saliency.

Industry collaboration

  • Siemens Healthcare - research in the area of medical imaging
  • QBSW - feasibility study of methods in video broadcasting (advertising detection)
  • Joanneum Research GmBH - research in the area of human visual attention

Academy collaboration

  • FEI STU - Prof. Polec
  • Fakulta matematiky, fyziky a informatiky UK - Dr. Elena Šikudová, Dr. Zuzana Černeková
  • TU Wien - Assoc. Prof. Ivan Viola, Manuela Waldner


Computer Vision and Computer Graphics Laboratory
Laboratory of Computer Vision and Graphics Working Group VGG - Vision & Graphics Group serves primarily for research activities and students have a opportunity to work on their team projects, diploma projects or bachelor projects in the laboratory. Instrumentation:

  • Optical see-through AR glasses (Vuzix STAR 1200XLD)
  • Head-mounted display headset (Oculus Rift)
  • Interactive transparent projection foil (UGO)
  • 3D monitor 27'' NVIDIA 3D Vision
  • Projectors (3D Vision) 144Hz (BenQ XL2720Z)
  • Nvidia 3D Vision Glasses
  • Nikon D810 full-frame DSLR camera with 36.3 MP (2x) including the lens: Nikon 14-24mm, Nikon 24-70mm, Nikon AF-S 70-200mm
  • High-speed camera 340 fps 2 MP resolution Basler acA2000-340kc
  • Light field camera LYTRO ILLUM
  • Accurate spectrophotometer Konica Minolta CM-2500d
  • RGB-D data acquisition using Kinect

Oculus Rift + Leap Motion sensor

Eye tracker: Eye Tracking Glasses SMI ETG 2 Wireless