@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{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}
}