The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Computer graphics, Rendering and Graphics hardware. His study in the field of Image processing, Computer graphics and Statistical model is also linked to topics like Arm muscle and Color depth. His work carried out in the field of Computer vision brings together such families of science as Animation and Texture memory.
His Computer graphics research is multidisciplinary, incorporating perspectives in 3D reconstruction, Segmentation, Frame rate and Motion capture. His Rendering research is multidisciplinary, incorporating elements of Wavefront, Ray, Geometrical optics, Data compression and Texture compression. His Graphics hardware research incorporates elements of Reflection, Feature detection and Real-time computer graphics.
His primary scientific interests are in Artificial intelligence, Computer vision, Computer graphics, Rendering and Visualization. Artificial intelligence is closely attributed to Perception in his study. Marcus Magnor regularly ties together related areas like Computer graphics in his Computer vision studies.
His research in 3D computer graphics and Real-time computer graphics are components of Computer graphics. His work in Computer graphics covers topics such as Video tracking which are related to areas like Motion compensation. In his research on the topic of Rendering, Tiled rendering is strongly related with Alternate frame rendering.
His primary areas of investigation include Artificial intelligence, Computer vision, Virtual reality, Rendering and Perception. His research in Artificial intelligence intersects with topics in Visual field and Reference frame. His research on Computer vision often connects related areas such as Computer graphics.
His biological study spans a wide range of topics, including Immersion, Peripheral vision and Oddball paradigm. His research integrates issues of HTML5, Codec, Computer graphics and Depth of field in his study of Rendering. His Perception study integrates concerns from other disciplines, such as Portrait, Deep learning and Face.
Marcus Magnor mainly investigates Artificial intelligence, Computer vision, Rendering, Pixel and Computer graphics. His Artificial intelligence study typically links adjacent topics like Perception. The various areas that Marcus Magnor examines in his Computer vision study include Animation and Reference frame.
His study on Rendering also encompasses disciplines like
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Free-viewpoint video of human actors
Joel Carranza;Christian Theobalt;Marcus A. Magnor;Hans-Peter Seidel.
international conference on computer graphics and interactive techniques (2003)
Multiview Imaging and 3DTV
Akira Kubota;Aljoscha Smolic;Marcus Magnor;Masayuki Tanimoto.
IEEE Signal Processing Magazine (2007)
Data compression for light-field rendering
M. Magnor;B. Girod.
IEEE Transactions on Circuits and Systems for Video Technology (2000)
Video Based Reconstruction of 3D People Models
Thiemo Alldieck;Marcus Magnor;Weipeng Xu;Christian Theobalt.
computer vision and pattern recognition (2018)
Time-resolved 3d capture of non-stationary gas flows
Bradley Atcheson;Ivo Ihrke;Wolfgang Heidrich;Art Tevs.
international conference on computer graphics and interactive techniques (2008)
Markerless Motion Capture using multiple Color-Depth Sensors
Kai Berger;Kai Ruhl;Yannic Schroeder;Christian Bruemmer.
vision modeling and visualization (2011)
Free-Viewpoint Video of Human Actors
Joel Carranza;Christian Theobalt;Marcus Magnor;Hans-Peter Seidel.
Untitled Event (2003)
Learning to Reconstruct People in Clothing From a Single RGB Camera
Thiemo Alldieck;Marcus Magnor;Bharat Lal Bhatnagar;Christian Theobalt.
computer vision and pattern recognition (2019)
Transparent and Specular Object Reconstruction
Ivo Ihrke;Kiriakos N. Kutulakos;Hendrik P. A. Lensch;Marcus A. Magnor.
Computer Graphics Forum (2010)
Tex2Shape: Detailed Full Human Body Geometry From a Single Image
Thiemo Alldieck;Gerard Pons-Moll;Christian Theobalt;Marcus Magnor.
international conference on computer vision (2019)
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