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Student Projects

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Displays Book (free image material)

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Spatial Augmented Reality Book (free ebook)

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VIOSO smartprojecting

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The Flagship Publication of the IEEE Computer Society

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The Caleydo Project

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Location - Computer Science Building (S3)

Location of the Institute for Computer Graphics: Computer Science Building (Science Park 3)

Position Indication:



The Institute of Computer Graphics carries out research in a modern field that has been coined "visual computing". Our core disciplines cover the imaging, processing, visualization and displaying of visual data. These are enabled by new fields and technologies, such as light fields, projector-camera systems, responsive optics, mobile computing, and visual analytics.

Please select one of the following topics or years for detailed information.


Mobile Museum Guidance using Relational Multi-Image Classification

We present a multi-image classification technique for mobile phones that is supported by relational reasoning. Users capture a sequence of images employing a simple near-far camera movement. After classifying distinct keyframes using a nearest-neighbor approach the corresponding database images are only considered for a majority voting if they exhibit similar near-far inter-image relations to the captured keyframes. In the context of PhoneGuide, our adaptive mobile museum guidance system, a user study revealed that our multi-image classification technique leads to significantly higher classification rates than single image classification. Furthermore, when using near-far image relations, less keyframes are sufficient for classification. This increases the overall classification speed of our approach by up to 35%.

Bruns, E. and Bimber, O., Mobile Museum Guidance through Relational Multi-Image Classification, International Conference on Multimedia and Ubiquitous Engineering (MUE’10), 2010, Best Paper Award

  • application/pdfManuscript (17.3 MB)
  • Localization and Classification through Adaptive Pathway Analysis

    We present an unobtrusive technique for supporting and improving object recognition approaches on mobile phones. To accomplish this we determine the present and future locations of museum visitors by evaluating user-generated spatio-temporal pathway data. In the context of our adaptive mobile museum guidance system called PhoneGuide we show that this improves the classification performance significantly and can achieve recognition rates comparable to those of traditional location-based image classification approaches. Over a period of four months, we collected the pathway data of 132 regular museum visitors at the Natural History Museum of Erfurt, Germany.

    Bruns, E. and Bimber, O., Localization and Classification through Adaptive Pathway Analysis, IEEE Pervasive Computing, 2010 (submitted: July 2009, accepted: August 2010), April-June issue, 2012

    • application/pdfManuscript (1.6 MB)
    • Closed-Loop Feedback Illumination for Optical Inverse Tone-Mapping in Light Microscopy

      We show that optical inverse tone-mapping (OITM) in light microscopy can improve the visibility of specimens, both when observed directly through the oculars and when imaged with a camera. In contrast to previous microscopy techniques, we pre-modulate the illumination based on the local modulation properties of the specimen itself. We explain how the modulation of uniform white light by a specimen can be estimated in real-time, even though the specimen is continuously but not uniformly illuminated. This information is processed and back-projected constantly, allowing the illumination to be adjusted on the fly if the specimen is moved or the focus or magnification of the microscope is changed. The contrast of the specimen's optical image can be enhanced, and high-intensity highlights can be suppressed. A formal pilot study with users indicates that this optimizes the visibility of spatial structures when observed through the oculars. We also demonstrate that the signal-to-noise (S/N) ratio in digital images of the specimen is higher if captured under an optimized rather than a uniform illumination. In contrast to advanced scanning techniques that maximize the S/N ratio using multiple measurements, our approach is fast because it requires only two images. This can be beneficial for image analysis in digital microscopy applications with real-time capturing demands.

      Bimber, O., Klöck, D., Amano, T., Grundhöfer, A., and Kurz, D., Closed-Loop Feedback Illumination for Optical Inverse Tone-Mapping in Light Microscopy, IEEE Transactions on Visualization and Computer Graphics, 2010 (submitted: August 2009, accepted: July 2010)

      • application/pdfManuscript (37.6 MB)