Refine
Year of publication
Document Type
- Conference Proceeding (34) (remove)
Has Fulltext
- yes (34) (remove)
Keywords
- 3D Extended Object Tracking (1)
- 3D shape tracking (1)
- Abtragsprinzip (1)
- Accelerometer (1)
- Automotive (1)
- Ballistocardiography (1)
- Bernstein polynomial (1)
- Biomedical Signal Capturing (1)
- Checkerboard ordering (2)
- Complex interval (1)
- Complex polynomial (1)
- Computational linguistics (1)
- Computer vision (1)
- Contactless measurement (1)
- Cyclic sign variation (1)
- Deep Learning (1)
- Dekontamination (1)
- Document image processing (1)
- Downsampling (1)
- Drowsiness (1)
- ECG (1)
- Elliptic Cylinder (1)
- Enclosure of the range (1)
- Energie (1)
- Entrepreneurship (1)
- Fourier-Chebyshev double series (1)
- GPU (1)
- Generative modeling (1)
- Handwriting recognition (1)
- Health monitoring (1)
- Industrial Ecology (1)
- Industrie (1)
- Internet of Things (1)
- Interval matrix (2)
- Interval property (1)
- IoT (1)
- Kreislaufwirtschaft (1)
- LCA (1)
- Learning (artificial intelligence) (1)
- Learning to cluster (1)
- LiDAR (1)
- Life Cycle Assessment (1)
- Literature Review (1)
- Machine Learning (1)
- Matrix interval (1)
- Multi-camera (1)
- Multivariate complex polynomial (1)
- Nachhaltige Entwicklung (1)
- Nachhaltigkeit (2)
- Perceptual grouping (1)
- Power and energy (1)
- Probabilistic forecasting (1)
- Probability (1)
- Real-time (1)
- Recurrent neural network (1)
- Renewable Energies (1)
- Runtime Reduction (1)
- Schneidprozess (1)
- Shape Tracking (1)
- Sign regular matrix (1)
- Sign variation (1)
- Sign-regular matrix (1)
- Sleep (1)
- Sleep monitoring (1)
- Smart Home (2)
- Smoke detector (1)
- Speaker clustering (1)
- Speaker recognition (1)
- Speech & image clustering (1)
- Stereo-matching (1)
- Stufenfräser (1)
- Störstelle (1)
- Sustainability (1)
- Technik (1)
- Text Mining (1)
- Totally nonnegative matrix (1)
- Totally positive matrix (1)
- Tourism (1)
- Umwelt (1)
- Umweltschutz (1)
- Uncertainty quantification and robustness (1)
Institute
- Fakultät Bauingenieurwesen (4)
- Fakultät Elektrotechnik und Informationstechnik (1)
- Fakultät Informatik (2)
- Fakultät Maschinenbau (2)
- Institut für Angewandte Forschung - IAF (3)
- Institut für Optische Systeme - IOS (5)
- Institut für Strategische Innovation und Technologiemanagement - IST (2)
- Institut für Systemdynamik - ISD (3)
- Institut für Werkstoffsystemtechnik Konstanz - WIK (1)
- Institut für Werkstoffsystemtechnik Thurgau - WITg (1)
Using multi-camera matching techniques for 3d reconstruction there is usually the trade-off between the quality of the computed depth map and the speed of the computations. Whereas high quality matching methods take several seconds to several minutes to compute a depth map for one set of images, real-time methods achieve only low quality results. In this paper we present a multi-camera matching method that runs in real-time and yields high resolution depth maps. Our method is based on a novel multi-level combination of normalized cross correlation, deformed matching windows based on the multi-level depth map information, and sub-pixel precise disparity maps. The whole process is implemented completely on the GPU. With this approach we can process four 0.7 megapixel images in 129 milliseconds to a full resolution 3d depth map. Our technique is tailored for the recognition of non-technical shapes, because our target application is face recognition.