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Over the past decades, a variety of spatial saliency methods have been introduced. Recently, motion saliency has gained much interests, where motion data estimated from an image sequence are utilized. In general, motion saliency requires reliable motion data as well as image segmentation for producing satisfactory saliency map which poses difficulty in most natural images. To overcome this, we propose a motion-based saliency generation that enhances the spatial saliency based on the combination of spatial and motion saliencies as well as motion complexity without the consideration of complex motion classification and image segmentation. Further, an affinity model is integrated for the purpose of connecting close-by pixels with different colors and obtaining a similar saliency. In experiment, we performed the proposed method on eleven test sets. From the objective performance evaluation, we validated that the proposed method produces better result than spatial saliency based on objective evaluation as well as ROC test.

Enhancement of Saliency Map Using Motion and Affinity Model