To increase the timeliness, objectivity, and efficiency in evaluating ophthalmology residents' learning of cataract surgery, an automatic analysis system for cataract surgery videos is developed to assess performance, particularly in the capsulorhexis step on the Kitaro simulator. We utilize computer vision technologies to measure performance of this critical step including duration, size, centrality, circularity, as well as motion stability during the capsulorhexis procedure. Consequently, a grading mechanism is established based on either linear regression or non-linear classification via Support Vector Machine of those computed measures. Comparisons of expert graders to the computer vision-based approach have demonstrated the accuracy and consistency of the computerized technique.
In this paper, we present two adaptive edge encoding schemes for the operational ratedistortion optimal polygon-based shape coding. The encoding edge is represented by an octant number, a major component, and a minor component, where the ranges of the two components are determined at two levels. For the object-level, these ranges are either determined by users or adaptive to the contour characteristics and the predefined admissible distortions using the discrete contour evolution method. For the edge-level, the range of the minor component is further adaptive to the magnitude of the major component. The appropriate code tables are selected for the two components according to their ranges. Experiments on MPEG-4 test sequences showed that our schemes outperform existing schemes in terms of bit-rate at the same distortion level.
The intention of shape coding in the MPEG-4 is to improve the coding efficiency as well as to facilitate the object-oriented applications, such as shape-based object recognition and retrieval. These require both efficient shape compression and effective shape description. Although these two issues have been intensively investigated in data compression and pattern recognition fields separately, it remains an open problem when both objectives need to be considered together. To achieve high coding gain, the operational rate-distortion optimal framework can be applied, but the direction restriction of the traditional eight-direction edge encoding structure reduces its compression efficiency and description effectiveness. We present two arbitrary direction edge encoding structures to relax this direction restriction. They consist of a sector number, a short component, and a long component, which represent both the direction and the magnitude information of an encoding edge. Experiments on both shape coding and hand gesture recognition validate that our structures can reduce a large number of encoding vertices and save up to 48.9% bits. Besides, the object contours are effectively described and suitable for the object-oriented applications.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.