@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}
}
@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}
}