1 research outputs found
ESAD: Endoscopic Surgeon Action Detection dataset
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 present
a frame-level action detection baseline model based on recent advances in object detection. Results on our new dataset show that our presented dataset
provides enough interesting challenges for future method and it can serve
as strong benchmark corresponding research in surgeon action detection in
endoscopic videos