CVFeb 9, 2019

Depth-Map Generation using Pixel Matching in Stereoscopic Pair of Images

arXiv:1902.03471v38 citations
AI Analysis

This work addresses the need for better 3D content creation in multimedia, though it appears incremental as it builds on existing depth-map generation approaches.

The paper tackles the problem of generating depth-maps from stereoscopic image pairs by proposing a new pixel-to-pixel matching algorithm, resulting in improved depth-maps compared to existing methods.

Modern day multimedia content generation and dissemination is moving towards the presentation of more and more `realistic' scenarios. The switch from 2-dimensional (2D) to 3-dimensional (3D) has been a major driving force in that direction. Over the recent past, a large number of approaches have been proposed for creating 3D images/videos most of which are based on the generation of depth-maps. This paper presents a new algorithm for obtaining depth information pertaining to a depicted scene from a set of available pair of stereoscopic images. The proposed algorithm performs a pixel-to-pixel matching of the two images in the stereo pair for estimation of depth. It is shown that the obtained depth-maps show improvements over the reported counterparts.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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