Segmentation of recorded endoscopic videos by detecting significant motion changes

In the medical domain it has become common to store recordings of endoscopic surgeries or procedures. The storage of these endoscopic videos provides not only evidence of the work of the surgeons but also facilitates research, the training of new surgeons and supports explanations to the patients. However, an endoscopic video archive, where tens or hundreds of new videos are added each day, needs content-based analysis in order to provide content-based search. A fundamental first step in content analysis is the segmentation of the video. We propose a new method for segmentation of endoscopic videos, based on spatial and temporal differences of motion in these videos. Through an evaluation with 20 videos we show that our approach provides reasonable performance.