About
I am currently a Master student in Computer Science at Jacobs University in Bremen, Germany. I am
a member of the Visualization
and Computer Graphics Group, lead by Prof. Linsen. My main
research interests include point-based rendering, visualization of
multi-variate volume data, and efficient iso-surface
rendering. Besides research, I'm hooked on tech entrepreneurship
and am part of team2x. In my
"free" time, I love to row.
Projects
A Cluster Hierarchy-based User Interface for Multi-variate
Volume Data Visualization
We propose a novel intuitive, yet powerful user interface for interactive visual exploration of multi-variate volume data. Our approach relies on hierarchical density-based clustering of the high-dimensional feature space. The result of the clustering is presented in a tree structure. The interface, apart from the volume rendering window, consists of two parts: a hierarchical tree widget and a parallel coordinates widget. The hierarchical tree widget employs a 2D radial layout of the cluster tree and provides intuitive techniques for assigning material properties to clusters, changing the size of clusters, and merging and splitting clusters. The linked parallel coordinates widget shows a representation of the selected clusters in parallel coordinates and allows for brushing of regions of interest. We automatically map the user selections to a proper multi-dimensional transfer function for 3D texture-based direct volume rendering. Since the user operates in cluster space, as opposed to transfer function space, the proposed approach is suitable for data with a feature space of arbitrarily high dimensionality and the complexity of the user interaction does not increase with the number of dimensions. We applied our methods to the visualization of multi-dimensional data consisting of multiple scalar fields as well as to single scalar fields, where the multi-dimensional feature space - besides the scalar values - includes first- and second-order derivative magnitudes.
Interactive Image-Space Point Cloud Rendering with Transparency and Shadows
In Proceedings of WSCG 2010.
We propose a method for point cloud rendering with transparency and shadows at interactive rates. Our approach does not require any global or local surface reconstruction method, but operates directly on the point cloud. All passes are executed in image space and no pre-computation steps are required. The underlying technique for our approach is a depth peeling method for point cloud surface representations. Having detected a sorted sequence of surface layers, they can be blended front to back with given opacity values to obtain renderings with transparency. These computation steps achieve interactive frame rates. For renderings with shadows, we determine a point cloud shadow texture that stores for each point of a point cloud whether it is lit by a given light source. The extraction of the layer of lit points is obtained using the depth peeling technique, again. For the shadow texture computation, we also apply a Monte-Carlo integration method to approximate light from an area light source, leading to soft shadows. Shadow computations for point light sources are executed at interactive frame rates. Shadow computations for area light sources are performed at interactive or near-interactive frame rates depending on the approximation quality.
Modeling of Large Cities - Visualization
Bachelor Thesis, Jacobs University, Bremen, Germany
There are a lot of existing Computer Aided Design (CAD) tools that help engineers and artists design rooms, buildings, or even whole residential areas, but there are very few that aid the design of an entire city. The proposed project aims to provide a tool that will enable users to model and then visualize large cities. During the modeling phase, the user is able to outline on a map the different areas (industrial, residential, commercial) that build up the city. After that the tool procedurally fills those areas with appropriate roads and buildings and in the final step visualizes the 3D model of the city. In visualization mode, the user is able to explore the city freely by changing camera position and orientation. Since displaying all buildings at once would require an enormous amount of resources, the tool also support different levels of details and employs rendering optimization techniques .
Robust Fusion of Dynamic Shape and Normal Capture for High-quality Reconstruction of Time-varying Geometry
In Proceedings of CVPR2008.
My contribution to this work was developed during an internship at Max-Plank Institute for Informatics, Saarbruecken, Germany. For more information on this project, please visit the website of Naveed Ahmed, who supervised me during my stay there.
We present a new passive approach to capture time-varying scene geometry in large acquisition volumes from multi-view video. It can be applied to reconstruct complete moving models of human actors that feature even slightest dynamic geometry detail, such as wrinkles and folds in clothing, and that can be viewed from 360 degrees. Starting from multi-view video streams recorded under calibrated lighting, we first perform marker-less human motion capture based on a smooth template with no high-frequency surface detail. Subsequently, surface reflectance and time-varying normal fields are estimated based on the coarse template shape. The main contribution of this work is a new statistical approach to solve the non-trivial problem of transforming the captured normal field that is defined over the smooth non-planar 3D template into true 3D displacements. Our spatio-temporal reconstruction method outputs displaced geometry that is accurate at each time step of video and temporally smooth, even if the input data are affected by noise.
We propose a novel intuitive, yet powerful user interface for interactive visual exploration of multi-variate volume data. Our approach relies on hierarchical density-based clustering of the high-dimensional feature space. The result of the clustering is presented in a tree structure. The interface, apart from the volume rendering window, consists of two parts: a hierarchical tree widget and a parallel coordinates widget. The hierarchical tree widget employs a 2D radial layout of the cluster tree and provides intuitive techniques for assigning material properties to clusters, changing the size of clusters, and merging and splitting clusters. The linked parallel coordinates widget shows a representation of the selected clusters in parallel coordinates and allows for brushing of regions of interest. We automatically map the user selections to a proper multi-dimensional transfer function for 3D texture-based direct volume rendering. Since the user operates in cluster space, as opposed to transfer function space, the proposed approach is suitable for data with a feature space of arbitrarily high dimensionality and the complexity of the user interaction does not increase with the number of dimensions. We applied our methods to the visualization of multi-dimensional data consisting of multiple scalar fields as well as to single scalar fields, where the multi-dimensional feature space - besides the scalar values - includes first- and second-order derivative magnitudes.
Interactive Image-Space Point Cloud Rendering with Transparency and Shadows
In Proceedings of WSCG 2010.
We propose a method for point cloud rendering with transparency and shadows at interactive rates. Our approach does not require any global or local surface reconstruction method, but operates directly on the point cloud. All passes are executed in image space and no pre-computation steps are required. The underlying technique for our approach is a depth peeling method for point cloud surface representations. Having detected a sorted sequence of surface layers, they can be blended front to back with given opacity values to obtain renderings with transparency. These computation steps achieve interactive frame rates. For renderings with shadows, we determine a point cloud shadow texture that stores for each point of a point cloud whether it is lit by a given light source. The extraction of the layer of lit points is obtained using the depth peeling technique, again. For the shadow texture computation, we also apply a Monte-Carlo integration method to approximate light from an area light source, leading to soft shadows. Shadow computations for point light sources are executed at interactive frame rates. Shadow computations for area light sources are performed at interactive or near-interactive frame rates depending on the approximation quality.
Modeling of Large Cities - Visualization
Bachelor Thesis, Jacobs University, Bremen, Germany
There are a lot of existing Computer Aided Design (CAD) tools that help engineers and artists design rooms, buildings, or even whole residential areas, but there are very few that aid the design of an entire city. The proposed project aims to provide a tool that will enable users to model and then visualize large cities. During the modeling phase, the user is able to outline on a map the different areas (industrial, residential, commercial) that build up the city. After that the tool procedurally fills those areas with appropriate roads and buildings and in the final step visualizes the 3D model of the city. In visualization mode, the user is able to explore the city freely by changing camera position and orientation. Since displaying all buildings at once would require an enormous amount of resources, the tool also support different levels of details and employs rendering optimization techniques .
Robust Fusion of Dynamic Shape and Normal Capture for High-quality Reconstruction of Time-varying Geometry
In Proceedings of CVPR2008.
My contribution to this work was developed during an internship at Max-Plank Institute for Informatics, Saarbruecken, Germany. For more information on this project, please visit the website of Naveed Ahmed, who supervised me during my stay there.
We present a new passive approach to capture time-varying scene geometry in large acquisition volumes from multi-view video. It can be applied to reconstruct complete moving models of human actors that feature even slightest dynamic geometry detail, such as wrinkles and folds in clothing, and that can be viewed from 360 degrees. Starting from multi-view video streams recorded under calibrated lighting, we first perform marker-less human motion capture based on a smooth template with no high-frequency surface detail. Subsequently, surface reflectance and time-varying normal fields are estimated based on the coarse template shape. The main contribution of this work is a new statistical approach to solve the non-trivial problem of transforming the captured normal field that is defined over the smooth non-planar 3D template into true 3D displacements. Our spatio-temporal reconstruction method outputs displaced geometry that is accurate at each time step of video and temporally smooth, even if the input data are affected by noise.
Publications
Petar Dobrev, Paul Rosenthal, Lars Linsen,
Interactive Image-Space Point Cloud Rendering with Transparency and Shadows, in Proc. of WSCG 2010. [bibtex]
Petar Dobrev, Sorin Stancu-Mara, Juergen Schoenwaelder,
Visualization of Node Interaction Dynamics in Network Traces, in Proc. of AIMS 2009. [bibtex]
Naveed Ahmed, Christian Theobalt, Petar Dobrev, Hans-Peter Seidel, Sebastian Thrun,
Robust Fusion of Dynamic Shape and Normal Capture for High-quality Reconstruction of Time-varying Geometry, in Proc. of CVPR 2008. [bibtex]
Interactive Image-Space Point Cloud Rendering with Transparency and Shadows, in Proc. of WSCG 2010. [bibtex]
Petar Dobrev, Sorin Stancu-Mara, Juergen Schoenwaelder,
Visualization of Node Interaction Dynamics in Network Traces, in Proc. of AIMS 2009. [bibtex]
Naveed Ahmed, Christian Theobalt, Petar Dobrev, Hans-Peter Seidel, Sebastian Thrun,
Robust Fusion of Dynamic Shape and Normal Capture for High-quality Reconstruction of Time-varying Geometry, in Proc. of CVPR 2008. [bibtex]
Contact
Email: p.dobrev@jacobs-university.de
Linked-in: http://de.linkedin.com/in/petardobrev
XING: https://www.xing.com/profile/Petar_Dobrev
Linked-in: http://de.linkedin.com/in/petardobrev
XING: https://www.xing.com/profile/Petar_Dobrev