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Deep stereoscopic image saliency inspired stereoscopic image thumbnail generation

Published: 01 December 2022 Publication History

Abstract

In this paper, we propose a stereoscopic image thumbnail generation method guided by the stereoscopic image saliency. Specifically, we utilize an uncertain-weighted fusion mechanism to combine the spatial saliency information with the saliency driven by depth cues, generating the dense stereoscopic saliency fixation map. Subsequently, the obtained dense fixation map is converted into a salient object map through a saliency optimization module, which provides the object-level saliency cues for the thumbnail generation task. Under the guidance of the obtained salient object map, a cropping window is employed to cut out the most salient region and generate the stereoscopic thumbnails, such that the disparity distribution of the original image can be well preserved, and avoid sharply deforming certain structured objects in the subsequent warping operation. Finally, the warping operation is utilized to adjust the aspect ratio of the stereoscopic thumbnail to the target size. Qualitative and quantitative results demonstrate that our proposed method achieves superior performance than the state-of-the-art benchmarks on the public datasets.

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Index Terms

  1. Deep stereoscopic image saliency inspired stereoscopic image thumbnail generation
        Index terms have been assigned to the content through auto-classification.

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        Published In

        cover image Multimedia Tools and Applications
        Multimedia Tools and Applications  Volume 81, Issue 29
        Dec 2022
        1540 pages

        Publisher

        Kluwer Academic Publishers

        United States

        Publication History

        Published: 01 December 2022
        Accepted: 13 July 2022
        Revision received: 27 September 2021
        Received: 30 June 2021

        Author Tags

        1. Stereoscopic saliency detection
        2. Stereoscopic thumbnail generation
        3. Energy minimization
        4. Uncertain weighted fusion

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