Objective evaluation of segmentation quality using spatio-temporal context
In this paper, we propose an automatic method for the objective evaluation of segmentation results. The method is based on computing the deviation of the segmentation results from a reference segmentation. The discrepancy between two results is weighted based on spatial and temporal contextual information, by taking into account the way humans perceive visual information. The metric is useful for applications where the final judge of the quality is a human observer or the results of segmentation are otherwise processed in a human-like fashion. The proposed evaluation has been applied both to automatically provide a ranking among different segmentation algorithms and to optimally set the parameters of a given algorithm.