@phdthesis{Coulon1997,
  author    = {Coulon, Carl-Helmut},
  title     = {Strukurorientiertes Fallbasiertes Schließen},
  doi       = {10.25643/bauhaus-universitaet.24},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20040212-265},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  year      = {1997},
  abstract  = {Das Ziel dieser Arbeit war es, durch Verwendung geeigneter vorhandener CAD-Pl{\"a}ne die Bearbeitung neuer CAD-Pl{\"a}ne zu unterst{\"u}tzen. Entstanden ist ein generischer Ansatz zum fallbasierten Schließens. Da in CAD-Pl{\"a}nen die r{\"a}umliche Struktur eine wichtige Rolle spielt, ist das Konzept auf strukturorientierte Anwendungen ausgerichtet. Deshalb bezeichne ich es als ein Konzept zum " strukturorientierten fallbasierten Schließen". Die Arbeit spezifiziert das Minimum an Wissen, welches zur Suche und Wiederverwendung von F{\"a}llen ben{\"o}tigt wird, wie das dar{\"u}ber hinausgehende Wissen verarbeitet wird, welche Zusammenh{\"a}nge es zum Beispiel zwischen Vergleichs- und Anpassungswissen gibt und wie man das Wissen modellieren kann. Zur Erl{\"a}uterung wird das ben{\"o}tigte Wissen anhand verschiedener Anwendungen dargestellt. Das in der Arbeit vorgestellte Konzept erlaubt die Erg{\"a}nzung, Detaillierung und Korrektur einer Anfrage. Die beiden entscheidenden Algorithmen dienen dem Vergleich von Anfrage und Fall und der Anpassung der Information des Falles zur Modifikation der Anfrage.},
  subject      = {Fallbasiertes Schließen},
  language  = {de}
}
@techreport{BrunsBrombachBimber2007,
  author    = {Bruns, Erich and Brombach, Benjamin and Bimber, Oliver},
  title     = {Mobile Phone Enabled Museum Guidance with Adaptive Classification},
  doi       = {10.25643/bauhaus-universitaet.940},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-9406},
  year      = {2007},
  abstract  = {Although audio guides are widely established in many museums, they suffer from several drawbacks compared to state-of-the-art multimedia technologies: First, they provide only audible information to museum visitors, while other forms of media presentation, such as reading text or video could be beneficial for museum guidance tasks. Second, they are not very intuitive. Reference numbers have to be manually keyed in by the visitor before information about the exhibit is provided. These numbers are either displayed on visible tags that are located near the exhibited objects, or are printed in brochures that have to be carried. Third, offering mobile guidance equipment to visitors leads to acquisition and maintenance costs that have to be covered by the museum. With our project PhoneGuide we aim at solving these problems by enabling the application of conventional camera-equipped mobile phones for museum guidance purposes. The advantages are obvious: First, today's off-the-shelf mobile phones offer a rich pallet of multimedia functionalities ---ranging from audio (over speaker or head-set) and video (graphics, images, movies) to simple tactile feedback (vibration). Second, integrated cameras, improvements in processor performance and more memory space enable supporting advanced computer vision algorithms. Instead of keying in reference numbers, objects can be recognized automatically by taking non-persistent photographs of them. This is more intuitive and saves museum curators from distributing and maintaining a large number of physical (visible or invisible) tags. Together with a few sensor-equipped reference tags only, computer vision based object recognition allows for the classification of single objects; whereas overlapping signal ranges of object-distinct active tags (such as RFID) would prevent the identification of individuals that are grouped closely together. Third, since we assume that museum visitors will be able to use their own devices, the acquisition and maintenance cost for museum-owned devices decreases.},
  subject      = {Objektverfolgung},
  language  = {en}
}
@techreport{BrunsBimber2007,
  author    = {Bruns, Erich and Bimber, Oliver},
  title     = {Adaptive Training of Video Sets for Image Recognition on Mobile Phones},
  doi       = {10.25643/bauhaus-universitaet.822},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-8223},
  year      = {2007},
  abstract  = {We present an enhancement towards adaptive video training for PhoneGuide, a digital museum guidance system for ordinary camera-equipped mobile phones. It enables museum visitors to identify exhibits by capturing photos of them. In this article, a combined solution of object recognition and pervasive tracking is extended to a client-server-system for improving data acquisition and for supporting scale-invariant object recognition.},
  subject      = {Objektverfolgung},
  language  = {en}
}