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A Method for Single-Stimulus Quality Assessment of Segmented Video

We present a unified method for single-stimulus quality assessment of segmented video. This method takes into consideration colour and motion features of a moving sequence and monitors their changes across segment boundaries. Features are estimated using a local neighbourhood which preserves the topological integrity of segment boundaries. Furthermore the proposed method addresses the problem of unreliable and/or unavailable feature estimates by applying normalized differential convolution (NDC). Our experimental results suggest that the proposed method outperforms competing methods in terms of sensitivity as well as noise immunity for a variety of standard test sequences.