I am now at Beuth University of Applied Science and until 2013 a PhD student working with the Computer Graphics Group at Technische Universität Berlin. I was advised by Marc Alexa. I am holding a Diploma from the Computer Science and Media programme of the Bauhaus University Weimar. During my studies I was visiting the University of British Columbia in Vancouver and the Max-Planck-Institut Informatik in Saarbrücken. My research interests span Digital Fabrication, Computer Graphics and Computer Vision. From August - October 2012 I have been visiting Disney Research Zurich.
From 2006-2009 I was working as a software developer at art+com AG in Berlin where I participated in the development of several innovative media installations. I am also co-founder of the 3D art+gallery platform kunstmatrix.
Feel free to email me. I can be reached at kristian.hildebrand at tu-berlin dot de
We present a novel application workflow to physically produce personalized objects by relying on the sketch-based input metaphor. This is achieved by combining different sketch-based retrieval and modeling aspects and optimizing the output for 3D printing technologies. The workflow starts from a user drawn 2D sketch that is used to query a large 3D shape database. A simple but powerful sketch-based modeling technique is employed to modify the result from the query. Taking into account the limitations of the additive manufacturing process we define a fabrication constraint deformation to produce personalized 3D printed objects.
Most additive manufacturing technologies work by slicing the shape and then generating each slice independently. This introduces an anisotropy into the process, often as different accuracies in the tangential and normal directions, but also in terms of other parameters such as build speed or tensile strength and strain. We model this as an anisotropic cubic element. Our approach then finds a compromise between modeling each part of the shape individually in the best possible direction and using one direction for the whole shape part. Then we optimize a decomposition of the shape along this basis so that each part can be consistently sliced along one of the basis vectors. In simulation, we show that this approach is superior to slicing the whole shape in one direction, only.
We introduce an algorithm and representation for fabricating 3D shape abstractions using mutually intersecting planar cut-outs. The planes have prefabricated slits at their intersections and are assembled by sliding them together. Based on an analysis of construction rules, we propose an extended binary space partitioning tree as an efficient representation of such cardboard models which allows us to quickly evaluate the feasibility of newly added planar elements. The complexity of insertion order quickly increases with the number of planar elements and manual analysis becomes intractable. We provide tools for generating cardboard sculptures with guaranteed constructibility.
We develop a system for 3D object retrieval based on sketched feature lines as input. For objective evaluation, we collect a large number of query sketches from human users that are related to an existing data base of objects. The sketches turn out to be generally quite abstract with large local and global deviations from the original shape. Based on this observation, we decide to use a bag-of-features approach over computer generated line drawings of the objects. We develop a targeted feature transform based on Gabor filters for this system. We can show objectively that this transform is better suited than other approaches from the literature developed for similar tasks. Moreover, we demonstrate how to optimize the parameters of our, as well as other approaches, based on the gathered sketches. In the resulting comparison, our approach is significantly better than any other system described so far.
For most image databases, browsing as a means of retrieval is impractical, and query based searching is required. Queries are often expressed as keywords (or by other means than the images themselves), requiring the images to be tagged. In view of the ever increasing size of image databases, the assumption of an appropriate and complete set of tags might be invalid, and content based search techniques become vital. We propose algorithms and specific image descriptors for sketch-based image retrieval.
We introduce Photosketcher, an interactive system for progressively synthesizing novel images using only sparse user sketches as the input. Compared to existing approaches for synthesising images from parts of other images, Photosketcher works on the image content exclusively, no keywords or other metadata associated with the images is required. Users sketch the rough shape of a desired image part and we automatically search a large collection of images for images containing that part. The search is based on a bag-of-features approach using local descriptors for translation invariant part retrieval. The compositing step again is based on user scribbles: from the scribbles we predict the desired part using Gaussian Mixture Models and compute an optimal seam using Graphcut.
We describe here an interactive visualization tool for realistically rendering the appearance of arbitrary 3D dust distributions surrounding one or more illuminating stars. Our rendering algorithm is based on the physical models used in astrophysics research. The tool can be used to create virtual fly-throughs of reflection nebulae for interactive desktop visualizations, or to produce scientifically accurate animations in planetarium shows. The algorithm is also applicable to investigate on-the-fly the visual effects of physical parameter variations, exploiting visualiza- tion technology to help gain a deeper and more intuitive understanding of the complex interaction of light and dust in real astrophysical settings.
We present a new visualization technique for the rendering of astronomical objects, like reflection nebulae and provide two approaches for reconstructing the volumetric structure of spiral galaxies from conventional 2D images. Our interactive visualization tool renders the physically correct, commonly very colorful, appearance of arbitrary three-dimensional interstellar dust distributions surrounding illuminating stars. The proposed reconstruction algorithm incorporates computerized tomography methods as well as far-infrared information to plausibly recover to the shape of spiral galaxies. With our GPU-based volume rendering driving a non-linear optimization, we estimate the galaxy’s dust density. The optimization refines the model by minimizing the differences between the rendered image and the original astronomical image.
We use an information visualization technique called 'accordion drawing' that guarantees three key properties: context, visibility, and frame rate. We provide context through the navigation metaphor of a rubber sheet that can be smoothly stretched to show more details in the areas of focus, while the surrounding regions of context are correspondingly shrunk. Landmarks, such as user specified motifs or differences between aligned base pairs across multiple sequences, are guaranteed to be visible even if located in the shrunken areas of context. Our graphics infrastructure for progressive rendering provides immediate responsiveness to user interaction by guaranteeing that we redraw the scene at a target frame rate.
We create virtual exhibition rooms for artists, gallerists and collections and combine these exhibitions to one website: www.kunstmatrix.com. For the first time, pictures, sculptures and installations will become an experience that is three-dimensional, atmospheric and as close to reality as possible in an internet browser – no additional software necessary.
Virtual exhibitions offer support for the flexible presentation and documentation of works of art and promote their selling. Via kunstmatrix artists, gallerists and art collectors can seize the opportunity to present a curated exhibition to an interested public, always up-to-date, comprehensive and individually designed.