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Accuracy in Depth Recovery and 3D Image Synthesis From Single Image Using Multi-Color Filter Aperture and Shallow Depth of Field

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PubDate: September 2021

Teams: R.V.College of Engineering

Writers: Rashmi R. Deshpande; Mahabaleswara Ram Bhatt; C. H. Renu Madhavi

PDF: Accuracy in Depth Recovery and 3D Image Synthesis From Single Image Using Multi-Color Filter Aperture and Shallow Depth of Field

Abstract

A computational 3D image generation using a single view with multi-color filter aperture (MCA) and multi-plane representation is a cost-effective approach and most useful when there is no option to acquire either stereo or multi-views with orientation at all. Although this approach generates 3D perception image that includes multiple objects with both similar and dissimilar colors having occluded by each other, it may be insufficient for virtual/augmented reality applications due to inaccurate depth. In this article, we obtain a more accurate geometric depth estimation by formulating a suitable relationship between inter-objects depth of the 3D scene in the depth-of-field (DoF) zone and its corresponding inter-image plane depths of a 3D perception image in depth-of-focus (DoFo) zone of a given camera under shallow DoF zone constraint. But, this shallow depth zone is configured to be dependent only on the focal distance between the lens and object while the remaining parameters such as aperture diameter, focal length, and sensor sensitivity are held at constant values. All-in-focus 3D perception image is synthesized from multi-plane images (MPIs) by utilizing the inter-image plane depths computed from the disparities caused across the boundaries and its smooth surface from image textures inside the respective boundaries of the 2D MCA image. The 2.1D sketch is used as a semantic segmentation technique to determine the number of objects in the 3D scene as one in-focus region and the rest as out-of-focus regions due to the circle of confusions (CoCs) on the fixed image sensor plane. The same enables both ordering of the image regions and identifying occlusion wherever applicable. An accurate depth 3D image is synthesized, replacing accurate inter-depths in place of inter-depth between MPIs used for 3D perception image. In the end, the paper summarizes few experimental validations for the proposed approach with some salient examples having depth gaps between 0.5cm to 10.5cm.

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