The paper presents a new approach of optimized vectorization to generate stylized artifacts such as drawings with a plotter or cutouts with a laser cutter. For this, we developed a methodology for transformations between raster and vector space. More over, we identify semiot...

This paper presents the color-dependent method of removing inter-view redundancy from multiview video. The pruning of input views decides which fragments of views are redundant, i.e., do not provide new information about the three-dimensional scene, as these fragments were already vis...

The purpose of this paper is to in detail describe and analyse a Fourier based handcrafted descriptor for word recognition. Especially, it is discussed how the Variability in the results can be analysed and visualised. This efficiency of the descriptor is evaluated for ...

Signed distance functions computed in discrete form from given RGB-D data as regular voxel grids can represent manifold shapes as the zero crossing of a trivariate function; the corresponding meshes can be derived by the Marching Cubes algorithm. However, 3D models automatically&...

Machine learning has become a standard tool in computer vision. Nowadays, neural networks are one of the most prominent representatives in this class of algorithms that usually require training and evaluation to work as desired. There exist a variety of evaluation metrics to...

In this paper, the authors describe two methods designed for reducing the spatiotemporal redundancy of the video within the MPEG Immersive video (MIV) encoder: patch occupation modification and cluster splitting. These methods allow optimizing two important parameters of the immersive ...

Registering partial point clouds is crucial in numerous applications in the field of robotics, vision, and graphics. For arbitrary configurations, the registration problem requires an initial global alignment, which is computationally expensive and often still requires refinement. In this ...

Neural scene representations, such as Neural Radiance Fields (NeRF), are based on training a multilayer perceptron (MLP) using a set of color images with known poses. An increasing number of devices now produce RGB-D(color + depth) information, which has been shown to be...

Deep learning applications are attracting considerable interest nowadays and image analysis pipelines are no exception. Benthic studies often rely on the subjective evaluation of video material recorded using underwater drones. The demand for automatic image segmentation and quantitative evaluation ar...

Optical sensors can capture dynamic environments and derive depth information in near real-time. The quality of these digital reconstructions is determined by factors like illumination, surface and texture conditions, sensing speed and other sensor characteristics as well as the sensor-obj...

We introduce a particle-based simulation method for granular material in interactive frame rates. We divide the simulation into two decoupled steps. In the first step, a relatively small number of particles is accurately simulated with a constraint-based method. Here, all collisions&#...

Semantic segmentation of 3D point cloud is an essential task for autonomous driving environment perception. The pipeline of most pointwise point cloud semantic segmentation methods includes points sampling, neighbor searching, feature aggregation, and classification. Neighbor searching method like K-neares...