基本信息
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职业迁徙
个人简介
Research Interests
Appoximately in reverse chronological order. You may also check related departmental demos/news.
perception for automotive, H2020 project Enable-S3.
vision for aerial robots, participating on MBZIRC.
Rescue robotics. Vision for outdoor rescue robots (UGV), Eurathlon/TRADR summer school, European (EU) projects TRADR, Nifti, CMP demos, NIFTi robot in Czech TV
Advanced predictors for object detection and tracking.
Learning for tracking and recognition.
Multicamera environments, Virtual Rooms. See also ViRoom, Blue-C.
(Multi-)Camera (self-)calibration. Free SW downloadable
Omnidirectional vision; Omnivis2004, The fifth Workshop on Omnidirectional Vision, Camera Networks and Non-classical cameras, In conjunction with ECCV2004.
Selected publications
Public profiles (as requested by area chairs of CVPR2012, and many others ...) [ Google Scholar profile | DBLP | ResearcherId | orcid.org ]
Publications [1994-2001,2004-], [2001-2003] in searchable archives. Put "svoboda" into the author field. List of (almost) all.
Search CMP database (BibTeX output)
M. Pecka, K. Zimmermann, M. Reinsten, and T. Svoboda. Controlling Robot Morphology from Incomplete Measurements. In IEEE Transactions on Industrial Electronics, accepted May 2016. [pdf (before proof read), IEEE Xplore]
V. Kubelka, L. Oswald, F. Pomerleau, F. Colas, T. Svoboda, and M. Reinstein. Robust data fusion of multi-modal sensory information for mobile robots. In Journal of Field Robotics, June 2015, Vol 32, Issue 4. [pdf]
K. Zimmermann, D. Hurych, T. Svoboda. Non-Rigid Object Detection with Local Interleaved Sequential Alignment (LISA). In IEEE Transactions on Pattern Analysis and Machine Intelligence, [pdf as accepted], April 2014, Vol 36, Issue 4
K. Zimmermann, D. Hurych, T. Svoboda. Exploiting Features -- Locally Interleaved Sequential Alignment for Object Detection. In 11th Asian Conference on Computer Vision - ACCV 2012, [pdf]
T. Petricek, T. Svoboda. Area-weighted Surface Normals for 3D Object Recognition. In 21st International Conference on Pattern Recognition - ICPR 2012 [pdf]
K. Zimmermann, T. Svoboda, J. Matas. Anytime learning for the NoSLLiP tracker. Image and Vision Computing. 27(11), 2009, [pdf]
K. Zimmermann, J. Matas, and T. Svoboda. Tracking by an Optimal Sequence of Linear Predictors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 31(4), 2009, [pdf]
K. Zimmermann, T. Svoboda, J. Matas. Simultaneous learning of motion and appearance. The 1st International Workshop on Machine Learning for Vision-based Motion Analysis, In conjunction with the 10th European Conference on Computer Vision 2008, [ paper | talk ].
K. Zimmernann, T. Svoboda, J. Matas. Adaptive Parameter Optimization for Real-time Tracking. In Proceedings of the Workshop on Non-rigid Registration and Tracking through Learning - NRTL 2007 (joint workshop with the ICCV 2007). [ paper ]
J. Matas, K.Zimmermann, T. Svoboda, A. Hilton. Learning Efficient Linear Predictors for Motion Estimation. In Proceedings of 5th Indian Conference on Computer Vision, Graphics and Image Processing. [ paper | talk ]
K.Zimmermann, T. Svoboda, J. Matas Multiview 3D Tracking with an Incrementally Constructed 3D Model, Third International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT), Chapel Hill, USA, 2006. DEMO
Tomas Svoboda, Daniel Martinec, and Tomas Pajdla. A convenient multi-camera self-calibration for virtual environments. PRESENCE: Teleoperators and Virtual Environments, pp 407-422, 14(4), August 2005. MIT Press Manuscript of the journal article [ PDF, 1.7MB ]. Its bib-entry.
Petr Doubek, Indra Geys, Tomas Svoboda, Luc Van Gool: Cinematographic Rules Applied to a Camera Network. In Omnivis 2004. [PDF].
研究兴趣
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arxiv(2023)
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2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (2023): 7643-7650
arxiv(2023)
IEEE Robotics and Automation Lettersno. 4 (2022): 3916-3921
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