Maximal Centroidal Vortices in Triangulations. A Descriptive Proximity Framework in Analyzing Object Shapes

M.Z. Ahmad, James Peters


This paper introduces a framework for approximating visual scene object shapes captured in sequences of video frames. To do this, we consider the hyper-connectedness of image object shapes by extending the Smirnov proximity measure to more than two sets. In this context, a shape is a finite, bounded planar region with a nonempty interior. The framework for this work is encapsulated in descriptive frame recurrence diagrams, introduced here. These diagrams offer a new approach in tracking the appearance and eventual disappearance of shapes in studying the persistence of object shapes in visual scenes. This framework is ideally suited for a machine intelligence approach to tracking the lifespans of visual scene structures captured in sequences of images in videos. A practical application of this framework is given in terms of the analysis of vehicular traffic patterns.


Hyper-connectedness, Object shape, Proximity, Recurrence, Vortices

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