Volume 28, Number 1-2 (2020) Domovská stránka kolekce Zobrazit statistiky

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Neigel, Peter , Ameli, Mina , Katrolia, Jigyasa , Feld, Hartmut , Wasenmüller, Oliver , Stricker, Didier
OPEDD: Off-Road Pedestrian Detection Dataset

The detection of pedestrians plays an essential part in the development of automated driver assistance systems. Many of the currently available datasets for pedestrian detection focus on urban environments. State-of-the-art neural networks trained on these datasets struggle in generalizing their ...

Glöckner, D.-Amadeus J. , Ihde, Lisa , Döllner, Jürgen , Trapp, Matthias
Intermediate Representations for Vectorization of Stylized Images

This paper presents a new approach for the vectorization of stylized images using intermediate data representations to interface image stylization and vectorization techniques. It enables the combination of efficient GPU-based implementations of interactive image stylization techniques and the advantages&#...

Benger, Werner , Leimer, Wolfgang , Baran, Ramona
Visualizing Massive Pristine LIDAR Amplitude Responses

Airborne light detection and ranging (LIDAR)- based bathymetry is a highly specialized field within the widely known and used geoscientific surveying technology based on green spectrum lasers. Green light can penetrate shallow water bodies such that river and lake beds can be surveyed.&...

Fischer, Roland , Dittmann, Philipp , Schröder, Christoph , Zachmann, Gabriel
Improved Lossless Depth Image Compression

Since RGB-D sensors became massively popular and are used in a wide range of applications, depth data compression became an important research topic. Live-streaming of depth data requires quick compression and decompression. Accurate preservation of information is crucial in order to prevent...

Napieralla, Jonah , Sundstedt, Veronica
Ultrawide Field of View by Curvilinear Projection Methods

The rectilinear Perspective projection produces natural-looking results on the condition that the degree of field of view (FoV) is narrow, as raising it causes an exponential increase in visual distortion. Curvilinear perspective projection methods that counter this issue exist in photography,&#x...

Tóth, Ákos , Kunkli, Roland
The Effects of Different Triangulation Techniques for Cage Based Image Deformation Using Generalized Barycentric Coordinates

In computer graphics, the generalized barycentric coordinates (GBC) are often used for image deformation. To manipulate an input image using a cage based image deformation method, we usually have to consider a source polygon with a triangulation; but defining the triangulation of the&#x...

Stefańczyk, Maciej , Bocheński, Tomasz
Mixing deep learning with classical vision for object recognition

Nowadays, when one needs a system for image recognition, it is mostly a matter of finding pre-trained CNN and, sometimes, adding additional training based on transferred knowledge. Accurate 6-DOF object localization in the image is a more laborious task and requires more complex tr...

Boltcheva, Dobrina , Basselin, Justine , Poull, Clément , Barthélemy, Hérvé , Sokolov, Dmitry
Topological-based roof modeling from 3D point clouds

Automatic extraction of building roofs from remote sensing data is important for many applications including 3D city modeling, urban planning, disaster management, and simulations. In this paper, we propose an automatic workflow for roof reconstruction by polygonal models from classified high-den...

Sommer, Alexander , Schwanecke, Ulrich , Schoemer, Elmar
Chebyshev’s Method on Projective Fluids

We demonstrate the acceleration potential of the Chebyshev semi-iterative approach for fluid simulations in Projective Dynamics. The Chebyshev approach has been successfully tested for deformable bodies, where the dynamical system behaves relatively linearly, even though Projective Dynamics, in general,&#x...

Wagner, Florian T. , Döllner, Jürgen , Trapp, Matthias
Real-time Service-based Stream-processing of High-resolution Videos

This paper reports on a service-based approach to enable real-time stream-processing of high-resolution videos. It presents a concept for integrating black-box image and video processing operations into a streaming framework. It further describes approaches to optimize data flow between the proce...

Cecchetto, Benjamin T. , Stewart, James
Reconstruction of Photon Distributions

We present an experimental setup to capture photon distributions from a liquid scattering medium and to reconstruct the flux density throughout the medium. The capture mechanism moves an occluder through the medium, which is illuminated by a laser. For each position of the occluder...

Reyes-Aviles, Fernando , Fleck, Philipp , Schmalstieg, Dieter , Arth, Clemens
Improving RGB Image Consistency for Depth-Camera

Indoor reconstruction using depth camera algorithms (e.g., InfiniTAMv3) is becoming increasingly popular. Simple reconstruction methods solely use the frames of the depth camera, leaving any imagery from the adjunct RGB camera untouched. Recent approaches also incorporate color camera information to&#...

Hammami, Amal , Hamida, Amal Ben , Amar, Chokri Ben , Nicolas, Henri
Regions Based Semi-fragile Watermarking Scheme

In this paper, we propose a new semi-fragile watermarking scheme in the frequency domain for surveillance videos authentication. Our system starts operating by generating a binary watermark based on a novel watermark construction process. This latter combines Speeded Up Robust Features (SURF...

Hast, Anders , Lind, Mats
Ensembles and Cascading of Embedded Prototype Subspace Classifiers

Deep learning approaches suffer from the so called interpretability problem and can therefore be very hard to visualise. Embedded Prototype Subspace Classifiers is one attempt in the field of explainable AI, which is both fast and efficient since it does not require repeated learni...

Feng, Qi , Shum, Hubert P. H. , Shimamura, Ryo , Morishima, Shigeo
Foreground-aware Dense Depth Estimation for 360 Images

With 360 imaging devices becoming widely accessible, omnidirectional content has gained popularity in multiple fields. The ability to estimate depth from a single omnidirectional image can benefit applications such as robotics navigation and virtual reality. However, existing depth estimation approach...

Scheer, Fabian , Neumann, Markus , Wirth, Konrad , Ginader, Marvin , Oezkurt, Yavuz , Mueller, Stefan
Evaluation of model-based tracking and its application in a robotic production line

The assessment of the accuracy and stability of model-based tracking approaches in the literature is a challenging task. Many of the presented methods lack a detailed evaluation or comparison to accurate ground truth data. Considering real world applications, it is hard to estimate ...

Frejlichowski, Dariusz
Application of a New Greyscale Descriptor for Recognition of Erythrocytes Extracted from Digital Microscopic Images

In the paper an algorithm for description of greyscale objects extracted from images is applied for recognition of human red blood cells visible on digital microscopic images. This is a part of an approach for automatic (or semiautomatic) diagnosis of selected diseases based on...

Kim, Jihwan , Choi, Sunghee
Hallucinating Very Low Resolution Face Images to 16x magnification with Age based Attributes

Face hallucination is a type of super resolution that restores very low resolution (8 8 pixel) to high resolution (128 128 pixel) face images. Since unique facial features caused by age, e.g.wrinkles, are ignored during restoration, restored face images can be somewhat dissimilar t...

Korpitsch, Thorsten , Takahashi, Shigeo , Gröller, Eduard , Wu, Hsiang-Yun
Simulated Annealing to Unfold 3D Meshes and Assign Glue Tabs

3D mesh unfolding transforms a 3D mesh model into one or multiple 2D planar patches. The technique is widely used to fabricate papercrafts, where 3D objects can be reconstructed from printed paper or paper-like materials. The applicability, visual quality, and stability of such pap...

Zwettler, Gerald A. , Holmes III, David R. , Backfrieder, Werner
Strategies for Training Deep Learning Models in Medical Domains with Small Reference Datasets

With the steady progress of Deep Learning (DL), powerful tools are now present for sophisticated segmentation tasks. Nevertheless, the generally very high demand for training data and precise reference segmentations often cannot be met in medical domains when processing small and individual&...

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