Motion-based video retrieval with application to computer-assisted retinal surgery.

In this paper, we address the problem of computer-aided ophthalmic surgery. In particular, a novel Content-Based Video Retrieval (CBVR) system is presented : given a video stream captured by a digital camera monitoring the current surgery, the system retrieves, within digital archives, videos that resemble the current surgery monitoring video. The search results may be used to guide surgeons' decisions, for example, let the surgeon know what a more experienced fellow worker would do in a similar situation. With this goal, we propose to use motion information contained in MPEG- 4 AVC/H.264 video standard to extract features from videos. We propose two approaches, one of which is based on motion histogram created for every frame of a compressed video sequence to extract motion direction and intensity statistics. The other combine segmentation and tracking to extract region displacements between consecutive frames and therefore characterize region trajectories. To compare videos, an extension of the fast dynamic time warping to multidimensional time series was adopted. The system is applied to a dataset of 69 video-recorded retinal surgery steps. Results are promising: the retrieval efficiency is higher than 69%.