  The amount of surgical data, recorded during video-monitored surgeries, has
extremely increased. This paper aims at improving existing solutions for the
automated analysis of cataract surgeries in real time. Through the analysis of
a video recording the operating table, it is possible to know which instruments
exit or enter the operating table, and therefore which ones are likely being
used by the surgeon. Combining these observations with observations from the
microscope video should enhance the overall performance of the systems. To this
end, the proposed solution is divided into two main parts: one to detect the
instruments at the beginning of the surgery and one to update the list of
instruments every time a change is detected in the scene. In the first part,
the goal is to separate the instruments from the background and from irrelevant
objects. For the second, we are interested in detecting the instruments that
appear and disappear whenever the surgeon interacts with the table. Experiments
on a dataset of 36 cataract surgeries validate the good performance of the
proposed solution.
