“Break Ames room illusion: depth from general single images” by Shi, Tao, Xu and Jia – ACM SIGGRAPH HISTORY ARCHIVES

“Break Ames room illusion: depth from general single images” by Shi, Tao, Xu and Jia

  • 2015 SA Technical Papers_Shi_Break Ames Room Illusion-Depth from General Single Images

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Title:

    Break Ames room illusion: depth from general single images

Session/Category Title:   Single Images

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Abstract:


    Photos compress 3D visual data to 2D. However, it is still possible to infer depth information even without sophisticated object learning. We propose a solution based on small-scale defocus blur inherent in optical lens and tackle the estimation problem by proposing a non-parametric matching scheme for natural images. It incorporates a matching prior with our newly constructed edgelet dataset using a non-local scheme, and includes semantic depth order cues for physically based inference. Several applications are enabled on natural images, including geometry based rendering and editing.

References:


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