Metrics for performance evaluation of video object segmentation and tracking without ground-truth

We present metrics to evaluate the performance of video object segmentation and tracking methods quantitatively when ground-truth segmentation maps are not available. The proposed metrics are based on the color and motion differences along the boundary of the estimated video object plane and the color histogram differences between the current object plane and its temporal neighbors. These metrics can be used to localize (spatially and/or temporally) regions where segmentation results are good or bad; or combined to yield a single numerical measure to indicate the goodness of the boundary segmentation and tracking results. Experimental results are presented to evaluate the segmentation map of the "Man" object in the "Hall Monitor" sequence both in terms of a single numerical measure, as well as localization of the good and bad segments of the boundary