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Opensea: open search based classification tool

Published: 12 June 2018 Publication History

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.

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Cited By

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  • (2020)HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopyScientific Data10.1038/s41597-020-00622-y7:1Online publication date: 28-Aug-2020

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cover image ACM Conferences
MMSys '18: Proceedings of the 9th ACM Multimedia Systems Conference
June 2018
604 pages
ISBN:9781450351928
DOI:10.1145/3204949
  • General Chair:
  • Pablo Cesar,
  • Program Chairs:
  • Michael Zink,
  • Niall Murray
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 12 June 2018

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Author Tags

  1. classification
  2. global features
  3. image
  4. indexing
  5. information retrieval
  6. machine learning
  7. video

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  • Research-article

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  • FRINATEK

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MMSys '18
Sponsor:
MMSys '18: 9th ACM Multimedia Systems Conference
June 12 - 15, 2018
Amsterdam, Netherlands

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Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

View all
  • (2020)HyperKvasir, a comprehensive multi-class image and video dataset for gastrointestinal endoscopyScientific Data10.1038/s41597-020-00622-y7:1Online publication date: 28-Aug-2020

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