ESAD: Endoscopic Surgeon Action Detection Dataset
Clicks: 111
ID: 282446
2020
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Abstract
In this work, we take aim towards increasing the effectiveness of surgical
assistant robots. We intended to make assistant robots safer by making them
aware about the actions of surgeon, so it can take appropriate assisting
actions. In other words, we aim to solve the problem of surgeon action
detection in endoscopic videos. To this, we introduce a challenging dataset for
surgeon action detection in real-world endoscopic videos. Action classes are
picked based on the feedback of surgeons and annotated by medical professional.
Given a video frame, we draw bounding box around surgical tool which is
performing action and label it with action label. Finally, we presenta
frame-level action detection baseline model based on recent advances in ob-ject
detection. Results on our new dataset show that our presented dataset provides
enough interesting challenges for future method and it can serveas strong
benchmark corresponding research in surgeon action detection in endoscopic
videos.
| Reference Key |
cuzzolin2020esad
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|---|---|
| Authors | Vivek Singh Bawa; Gurkirt Singh; Francis KapingA; Inna Skarga-Bandurova; Alice Leporini; Carmela Landolfo; Armando Stabile; Francesco Setti; Riccardo Muradore; Elettra Oleari; Fabio Cuzzolin |
| Journal | arXiv |
| Year | 2020 |
| DOI |
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