@techreport{AmanoBimberGrundhoefer2010,
  author    = {Amano, Toshiyuki and Bimber, Oliver and Grundh{\"o}fer, Anselm},
  title     = {Appearance Enhancement for Visually Impaired with Projector Camera Feedback},
  doi       = {10.25643/bauhaus-universitaet.1411},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20100106-14974},
  year      = {2010},
  abstract  = {Visually impaired is a common problem for human life in the world wide. The projector-based AR technique has ability to change appearance of real object, and it can help to improve visibility for visually impaired. We propose a new framework for the appearance enhancement with the projector camera system that employed model predictive controller. This framework enables arbitrary image processing such as photo-retouch software in the real world and it helps to improve visibility for visually impaired. In this article, we show the appearance enhancement result of Peli's method and Wolffshon's method for the low vision, Jefferson's method for color vision deficiencies. Through experiment results, the potential of our method to enhance the appearance for visually impaired was confirmed as same as appearance enhancement for the digital image and television viewing.},
  subject      = {Maschinelles Sehen},
  language  = {en}
}
@phdthesis{Grundhoefer2010,
  author    = {Grundh{\"o}fer, Anselm},
  title     = {Synchronized Illumination Modulation for Digital Video Compositing},
  doi       = {10.25643/bauhaus-universitaet.1440},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20101210-15278},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {2010},
  abstract  = {Informationsaustausch ist eines der Grundbed{\"u}rfnisse der Menschen. W{\"a}hrend fr{\"u}her dazu Wandmalereien,Handschrift, Buchdruck und Malerei eingesetzt wurden, begann man sp{\"a}ter, Bildfolgen zu erstellen, die als sogenanntes "Daumenkino" den Eindruck einer Animation vermitteln. Diese wurden schnell durch den Einsatz rotierender Bildscheiben, auf denen mit Hilfe von Schlitzblenden, Spiegeln oder Optiken eine Animation sichtbar wurde, automatisiert - mit sogenannten Phenakistiskopen,Zoetropen oder Praxinoskopen. Mit der Erfindung der Fotografie begannen in der zweiten H{\"a}lfte des 19. Jahrhunderts die ersten Wissenschaftler wie Eadweard Muybridge, Etienne-Jules Marey und Ottomar Ansch{\"u}tz, Serienbildaufnahmen zu erstellen und diese dann in schneller Abfolge, als Film, abzuspielen. Mit dem Beginn der Filmproduktion wurden auch die ersten Versuche unternommen, mit Hilfe dieser neuen Technik spezielle visuelle Effekte zu generieren, um damit die Immersion der Bewegtbildproduktionen weiter zu erh{\"o}hen. W{\"a}hrend diese Effekte in der analogen Phase der Filmproduktion bis in die achtziger Jahre des 20.Jahrhunderts recht beschr{\"a}nkt und sehr aufwendig mit einem enormen manuellen Arbeitsaufwand erzeugt werden mussten, gewannen sie mit der sich rapide beschleunigenden Entwicklung der Halbleitertechnologie und der daraus resultierenden vereinfachten digitalen Bearbeitung immer mehr an Bedeutung. Die enormen M{\"o}glichkeiten, die mit der verlustlosen Nachbearbeitung in Kombination mit fotorealistischen, dreidimensionalen Renderings entstanden, f{\"u}hrten dazu, dass nahezu alle heute produzierten Filme eine Vielfalt an digitalen Videokompositionseffekten beinhalten. ...},
  subject      = {Lumineszenzdiode},
  language  = {en}
}
@phdthesis{Bruns2010,
  author    = {Bruns, Erich},
  title     = {Adaptive Image Classification on Mobile Phones},
  doi       = {10.25643/bauhaus-universitaet.1421},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20100707-15092},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {2010},
  abstract  = {The advent of high-performance mobile phones has opened up the opportunity to develop new context-aware applications for everyday life. In particular, applications for context-aware information retrieval in conjunction with image-based object recognition have become a focal area of recent research. In this thesis we introduce an adaptive mobile museum guidance system that allows visitors in a museum to identify exhibits by taking a picture with their mobile phone. Besides approaches to object recognition, we present different adaptation techniques that improve classification performance. After providing a comprehensive background of context-aware mobile information systems in general, we present an on-device object recognition algorithm and show how its classification performance can be improved by capturing multiple images of a single exhibit. To accomplish this, we combine the classification results of the individual pictures and consider the perspective relations among the retrieved database images. In order to identify multiple exhibits in pictures we present an approach that uses the spatial relationships among the objects in images. They make it possible to infer and validate the locations of undetected objects relative to the detected ones and additionally improve classification performance. To cope with environmental influences, we introduce an adaptation technique that establishes ad-hoc wireless networks among the visitors' mobile devices to exchange classification data. This ensures constant classification rates under varying illumination levels and changing object placement. Finally, in addition to localization using RF-technology, we present an adaptation technique that uses user-generated spatio-temporal pathway data for person movement prediction. Based on the history of previously visited exhibits, the algorithm determines possible future locations and incorporates these predictions into the object classification process. This increases classification performance and offers benefits comparable to traditional localization approaches but without the need for additional hardware. Through multiple field studies and laboratory experiments we demonstrate the benefits of each approach and show how they influence the overall classification rate.},
  subject      = {Kontextbezogenes System},
  language  = {en}
}
@article{BimberIwai2009,
  author    = {Bimber, Oliver and Iwai, Daisuke},
  title     = {Superimposing Dynamic Range},
  series = {Eurographics 2009},
  journal   = {Eurographics 2009},
  doi       = {10.25643/bauhaus-universitaet.1532},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20120130-15325},
  year      = {2009},
  abstract  = {Replacing a uniform illumination by a high-frequent illumination enhances the contrast of observed and captured images. We modulate spatially and temporally multiplexed (projected) light with reflective or transmissive matter to achieve high dynamic range visualizations of radiological images on printed paper or ePaper, and to boost the optical contrast of images viewed or imaged with light microscopes.},
  subject      = {CGI <Computergraphik>},
  language  = {en}
}
@techreport{ExnerBrunsKurzetal.2009,
  author    = {Exner, David and Bruns, Erich and Kurz, Daniel and Grundh{\"o}fer, Anselm and Bimber, Oliver},
  title     = {Fast and Reliable CAMShift Tracking},
  organization    = {JP AUgmented Reality, Bauhaus-Universit{\"a}t Weimar},
  doi       = {10.25643/bauhaus-universitaet.1410},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20091217-14962},
  year      = {2009},
  abstract  = {CAMShift is a well-established and fundamental algorithm for kernel-based visual object tracking. While it performs well with objects that have a simple and constant appearance, it is not robust in more complex cases. As it solely relies on back projected probabilities it can fail in cases when the object's appearance changes (e.g. due to object or camera movement, or due to lighting changes), when similarly colored objects have to be re-detected or when they cross their trajectories. We propose extensions to CAMShift that address and resolve all of these problems. They allow the accumulation of multiple histograms to model more complex object appearance and the continuous monitoring of object identi- ties to handle ambiguous cases of partial or full occlusion. Most steps of our method are carried out on the GPU for achieving real-time tracking of multiple targets simultaneously. We explain an ecient GPU implementations of histogram generation, probability back projection, im- age moments computations, and histogram intersection. All of these techniques make full use of a GPU's high parallelization.},
  subject      = {Bildverarbeitung},
  language  = {en}
}
@techreport{GrundhoeferBimber2008,
  author    = {Grundh{\"o}fer, Anselm and Bimber, Oliver},
  title     = {Dynamic Bluescreens},
  doi       = {10.25643/bauhaus-universitaet.1233},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20080226-13016},
  year      = {2008},
  abstract  = {Blue screens and chroma keying technology are essential for digital video composition. Professional studios apply tracking technology to record the camera path for perspective augmentations of the original video footage. Although this technology is well established, it does not offer a great deal of flexibility. For shootings at non-studio sets, physical blue screens might have to be installed, or parts have to be recorded in a studio separately. We present a simple and flexible way of projecting corrected keying colors onto arbitrary diffuse surfaces using synchronized projectors and radiometric compensation. Thereby, the reflectance of the underlying real surface is neutralized. A temporal multiplexing between projection and flash illumination allows capturing the fully lit scene, while still being able to key the foreground objects. In addition, we embed spatial codes into the projected key image to enable the tracking of the camera. Furthermore, the reconstruction of the scene geometry is implicitly supported.},
  subject      = {Association for Computing Machinery / Special Interest Group on Graphics},
  language  = {en}
}
@techreport{BimberIwai2008,
  author    = {Bimber, Oliver and Iwai, Daisuke},
  title     = {Superimposing Dynamic Range},
  doi       = {10.25643/bauhaus-universitaet.1287},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20080422-13585},
  year      = {2008},
  abstract  = {We present a simple and cost-efficient way of extending contrast, perceived tonal resolution, and the color space of static hardcopy images, beyond the capabilities of hardcopy devices or low-dynamic range displays alone. A calibrated projector-camera system is applied for automatic registration, scanning and superimposition of hardcopies. We explain how high-dynamic range content can be split for linear devices with different capabilities, how luminance quantization can be optimized with respect to the non-linear response of the human visual system as well as for the discrete nature of the applied modulation devices; and how inverse tone-mapping can be adapted in case only untreated hardcopies and softcopies (such as regular photographs) are available. We believe that our approach has the potential to complement hardcopy-based technologies, such as X-ray prints for filmless imaging, in domains that operate with high quality static image content, like radiology and other medical fields, or astronomy.},
  subject      = {Bildverarbeitung},
  language  = {en}
}
@article{BrunsBimber2008,
  author    = {Bruns, Erich and Bimber, Oliver},
  title     = {Phone-to-Phone Communication for Adaptive Image Classification},
  doi       = {10.25643/bauhaus-universitaet.1296},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20080722-13685},
  year      = {2008},
  abstract  = {In this paper, we present a novel technique for adapting local image classifiers that are applied for object recognition on mobile phones through ad-hoc network communication between the devices. By continuously accumulating and exchanging collected user feedback among devices that are located within signal range, we show that our approach improves the overall classification rate and adapts to dynamic changes quickly. This technique is applied in the context of PhoneGuide - a mobile phone based museum guidance framework that combines pervasive tracking and local object recognition for identifying a large number of objects in uncontrolled museum environments.},
  subject      = {Peer-to-Peer-Netz},
  language  = {en}
}
@techreport{GrosseBimber2008,
  author    = {Grosse, Max and Bimber, Oliver},
  title     = {Coded Aperture Projection},
  doi       = {10.25643/bauhaus-universitaet.1234},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20080227-13020},
  year      = {2008},
  abstract  = {In computer vision, optical defocus is often described as convolution with a filter kernel that corresponds to an image of the aperture being used by the imaging device. The degree of defocus correlates to the scale of the kernel. Convolving an image with the inverse aperture kernel will digitally sharpen the image and consequently compensate optical defocus. This is referred to as deconvolution or inverse filtering. In frequency domain, the reciprocal of the filter kernel is its inverse, and deconvolution reduces to a division. Low magnitudes in the Fourier transform of the aperture image, however, lead to intensity values in spatial domain that exceed the displayable range. Therefore, the corresponding frequencies are not considered, which then results in visible ringing artifacts in the final projection. This is the main limitation of previous approaches, since in frequency domain the Gaussian PSF of spherical apertures does contain a large fraction of low Fourier magnitudes. Applying only small kernel scales will reduce the number of low Fourier magnitudes (and consequently the ringing artifacts) -- but will also lead only to minor focus improvements. To overcome this problem, we apply a coded aperture whose Fourier transform has less low magnitudes initially. Consequently, more frequencies are retained and more image details are reconstructed.},
  subject      = {Association for Computing Machinery / Special Interest Group on Graphics},
  language  = {en}
}
@article{BrombachBrunsBimber2008,
  author    = {Brombach, Benjamin and Bruns, Erich and Bimber, Oliver},
  title     = {Subobject Detection through Spatial Relationships on Mobile Phones},
  doi       = {10.25643/bauhaus-universitaet.1353},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20081007-14296},
  year      = {2008},
  abstract  = {We present a novel image classification technique for detecting multiple objects (called subobjects) in a single image. In addition to image classifiers, we apply spatial relationships among the subobjects to verify and to predict locations of detected and undetected subobjects, respectively. By continuously refining the spatial relationships throughout the detection process, even locations of completely occluded exhibits can be determined. Finally, all detected subobjects are labeled and the user can select the object of interest for retrieving corresponding multimedia information. This approach is applied in the context of PhoneGuide, an adaptive museum guidance system for camera-equipped mobile phones. We show that the recognition of subobjects using spatial relationships is up to 68\% faster than related approaches without spatial relationships. Results of a field experiment in a local museum illustrate that unexperienced users reach an average recognition rate for subobjects of 85.6\% under realistic conditions.},
  subject      = {Objekterkennung},
  language  = {en}
}