% Zeno Albisser
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@InProceedings{Pogorelov2018,
  title = {Opensea: open search based classification tool},
  author = {Konstantin Pogorelov and Zeno Albisser and Olga Ostroukhova and Mathias Lux and Dag Johansen and Pal Halvorsen and Michael Riegler},
  booktitle = {MMSys '18 Proceedings of the 9th ACM Multimedia Systems Conference},
  year = {2018},
  address = {New York (NY)},
  month = {Juni},
  pages = {363--368},
  publisher = {ACM Press},
  abstract = {This paper presents an open-source classification tool for image and video frame classification. The classification takes a search-based approach and relies on global and local image features. It has been shown to work with images as well as videos, and is able to perform the classification of video frames in real-time so that the output can be used while the video is recorded, playing, or streamed. OpenSea has been proven to perform comparable to state-of-the-art methods such as deep learning, at the same time performing much faster in terms of processing speed, and can be therefore seen as an easy to get and hard to beat baseline. We present a detailed description of the software, its installation and use. As a use case, we demonstrate the classification of polyps in colonoscopy videos based on a publicly available dataset. We conduct leave-one-out-cross-validation to show the potential of the software in terms of classification time and accuracy.},
  doi = {10.1145/3204949.3208128},
  url = {https://dl.acm.org/citation.cfm?id=3208128}
}