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.
Keywords:
Medical Imaging, Object Detection and Object Recognition in 2D / 3D, Visual Attention Prediction, Augmented and Virtual Reality Applications, Big Data Visualization
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.
AYUGUN, R.S. - BENEŠOVÁ, Vanda
Multimedia Retrieval that Works. 2018 IEEE Conf. Multimed. Inf. Process. Retr., 2018, pp. 63–68.
MARTÁK, Lukáš Samuel - ŠAJGALÍK, Mário - BENEŠOVÁ, Vanda
Polyphonic Note
Transcription of Time-Domain Audio Signal with Deep WaveNet Architecture. 2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP), pp. 1–5, 2018.
HUDEC, Ladislav - BENEŠOVÁ, Vanda
Texture Similarity Evaluation via Siamese Convolutional Neural Network. 2018 25th International Conference on Systems, Signals and Image Processing (IWSSIP), pp. 1-5, 2018.
TAMAJKA, Martin - BENEŠOVÁ, Vanda
Supervoxel Algorithm for Medical Image Processing. 2017 IEEE Int. Conf. Power, Control. Signals Instrum. Eng, pp. 3121-3127, 2017.
OLEŠOVÁ V. - BENEŠOVÁ, Vanda - POLATSEK, Patrik
Visual Attention in Egocentric Field-of-view using RGB-D Data. Proceedings Ninth International Conference on Machine Vision (ICMV 2016), 18th November, 2016, Nice, France. 1. vyd : SPIE - The International Society for Optical Engineering, 2017.
FOGELTON, Andrej - BENEŠOVÁ, Wanda
Eye blink detection based on motion vectors analysis. Computer Vision and Image Understanding, 0, pp. 1–11. 2016. http://doi.org/10.1016/j.cviu.2016.03.011
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 http://doi.org/10.1109/IWSSIP.2016.7502725
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. http://doi.org/10.1109/LSP.2016.2523339
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. http://doi.org/10.1117/1.JEI.25.6.061413
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.
JAKAB, Marek - BENEŠOVÁ, Vanda - RAČEV, Marek
3D Object Recognition based on Local Descriptors. IS&T/SPIE Electronic Imaging 2015. San Francisco, USA: SPIE. 2015
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. http://doi.org/10.1016/j.chb.2014.11.093
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. http://doi.org/10.1145/2788539.2788557
UHLÍKOVÁ, Ivana - BENEŠOVÁ, Vanda - POLEC, Jaroslav - CSÓKA, Tibor
Texture Aware Image Error Concealment. EUROCON 2015. Salamanca, Spain: IEEE Catalog Number: CFP15EUR-CDR. 2015
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.
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. http://doi.org/10.1117/12.905813
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. http://doi.org/10.1007/978-1-4419-0953-4
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. http://doi.org/10.1109/ICCVW.2009.5457615
KAPEC, Peter - BRNDIAROVÁ, G., GLOGER, M., MARÁK, J.
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.
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
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.
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
Infrastructure
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
