Dr. Florian Baumann
Dr. Florian Baumann
Dell Technologies
Vahvistettu sähköpostiosoite verkkotunnuksessa dell.com - Kotisivu
Recognizing human actions using novel space-time volume binary patterns
F Baumann, A Ehlers, B Rosenhahn, J Liao
Neurocomputing 173, 54-63, 2016
Motion Binary Patterns for Action Recognition.
F Baumann, J Lao, A Ehlers, B Rosenhahn, MY Yang
ICPRAM, 385-392, 2014
Action recognition with hog-of features
F Baumann
German Conference on Pattern Recognition, 243-248, 2013
Cascaded random forest for fast object detection
F Baumann, A Ehlers, K Vogt, B Rosenhahn
Scandinavian Conference on Image Analysis, 131-142, 2013
Computation strategies for volume local binary patterns applied to action recognition
F Baumann, A Ehlers, B Rosenhahn, J Liao
2014 11th IEEE International Conference on Advanced Video and Signal Based …, 2014
SoundScript-Supporting the acquisition of character writing by multisensory integration
AO Effenberg, G Schmitz, F Baumann, B Rosenhahn, D Kroeger
Open Psychology Journal 8 (2015), Nr. 1 8 (1), 230-237, 2015
Ego-motion compensated face detection on a mobile device
B Scheuermann, A Ehlers, H Riazy, F Baumann, B Rosenhahn
CVPR 2011 WORKSHOPS, 66-71, 2011
Symmetry enhanced adaboost
F Baumann, K Ernst, A Ehlers, B Rosenhahn
International Symposium on Visual Computing, 286-295, 2010
Boosted fractal integral paths for object detection
A Ehlers, F Baumann, B Rosenhahn
International Symposium on Visual Computing, 458-470, 2014
Thresholding a Random Forest Classifier
F Baumann, F Li, A Ehlers, B Rosenhahn
Device and method for producing a three-dimensional object with a fibre feeding device
E Duffner, F Baumann
US Patent App. 16/062,311, 2018
MedianStruck for long-term tracking applications
F Baumann, E Dayangac, J Aulinas, M Zobel
2016 Sixth International Conference on Image Processing Theory, Tools and …, 2016
Target Position and Speed Estimation Using LiDAR
E Dayangac, F Baumann, J Aulinas, M Zobel
International Conference on Image Analysis and Recognition, 470-477, 2016
Improved Threshold Selection by Using Calibrated Probabilities for Random Forest Classifiers
F Baumann, J Chen, K Vogt, B Rosenhahn
2015 12th Conference on Computer and Robot Vision, 155-160, 2015
On-the-fly handwriting recognition using a high-level representation
C Reinders, F Baumann, B Scheuermann, A Ehlers, N Mühlpforte, ...
International Conference on Computer Analysis of Images and Patterns, 1-13, 2015
Sequential boosting for learning a random forest classifier
F Baumann, A Ehlers, B Rosenhahn, W Liu
2015 IEEE Winter Conference on Applications of Computer Vision, 442-447, 2015
Multi-sensor Acceleration-Based Action Recognition
F Baumann, I Schulz, B Rosenhahn
International Conference Image Analysis and Recognition, 48-57, 2014
Exploiting object characteristics using custom features for boosting-based classification
A Ehlers, F Baumann, B Rosenhahn
Scandinavian Conference on Image Analysis, 420-431, 2013
Probabilistic nodes for modelling classification uncertainty for random forest
F Baumann, K Vogt, A Ehlers, B Rosenhahn
2015 14th IAPR International Conference on Machine Vision Applications (MVA …, 2015
Random Forests and Their Applications in Scene Understanding
F Baumann
VDI Verlag GmbH, 2015
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Artikkelit 1–20