TY - RPRT A1 - Bruns, Erich A1 - Bimber, Oliver T1 - Adaptive Training of Video Sets for Image Recognition on Mobile Phones N2 - 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. KW - Objektverfolgung KW - Neuronales Netz KW - Handy KW - Objekterkennung KW - Museum KW - Anpassung KW - mobile phones KW - object recognition KW - neural networks KW - museum guidance KW - pervasive tracking KW - temporal adaptation Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-8223 ER - TY - RPRT A1 - Bruns, Erich A1 - Brombach, Benjamin A1 - Bimber, Oliver T1 - Mobile Phone Enabled Museum Guidance with Adaptive Classification N2 - 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. KW - Objektverfolgung KW - Neuronales Netz KW - Handy KW - Objekterkennung KW - Museum KW - Anpassung KW - Mobiltelefone KW - Museumsführer KW - Adaptive Klassifizierung KW - Ad-hoc Sensor-Netzwerke KW - mobile phones KW - object recognition KW - museum guidance KW - adaptive classification KW - ad-hoc sensor networks Y1 - 2007 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20111215-9406 ER - TY - THES A1 - Coulon, Carl-Helmut T1 - Strukurorientiertes Fallbasiertes Schließen T1 - Structure oriented case based reasoning N2 - Das Ziel dieser Arbeit war es, durch Verwendung geeigneter vorhandener CAD-Pläne die Bearbeitung neuer CAD-Pläne zu unterstützen. Entstanden ist ein generischer Ansatz zum fallbasierten Schließens. Da in CAD-Plänen die räumliche 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 Fällen benötigt wird, wie das darüber hinausgehende Wissen verarbeitet wird, welche Zusammenhänge es zum Beispiel zwischen Vergleichs- und Anpassungswissen gibt und wie man das Wissen modellieren kann. Zur Erläuterung wird das benötigte Wissen anhand verschiedener Anwendungen dargestellt. Das in der Arbeit vorgestellte Konzept erlaubt die Ergänzung, 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. N2 - The task of this thesis was the computer supported reuse of known CAD-designs in order to create new CAD-designs. The developed solution contains a generic approach to case based reasoning. Due to the relevance of spatial structures in CAD-designs the approach focusses on structure oriented applications. Therefore it is called an approach for „structure oriented case based reasoning". This thesis specifies the kind of the minimum knowledge required for retrieval and reuse of cases, how to integrate additional knowledge, relations between knowledge needed for comparision and adaption and how to model the knowledge. For illustration the required knowledge is described for different applications. The developed concept allows to extend, detail and correct a given query. The two most important algorithms are used to compare cases and query and to reuse the information found in a case to modify a query. KW - Fallbasiertes Schließen KW - Bauplanung KW - CAD KW - Problemlösen KW - Wissensmodellierung KW - Strukturvergleich KW - Anpassung KW - Knowledge modelling KW - comparison of structure KW - adaption Y1 - 1997 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20040212-265 ER -