基于摄像机阵列多深度线索的场景深度估计及优化方法

项目名称： 基于摄像机阵列多深度线索的场景深度估计及优化方法

项目编号： No.61272287

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 王庆

作者单位： 西北工业大学

项目金额： 81万元

中文摘要： 计算机视觉三维重建与人类视觉心理学研究表明，多线索深度估计与单一线索深度估计相比具有较大优势。本项目以密集型摄像机阵列为实验平台，从场景的多视点采样数据和虚拟孔径合成数据中提取多种深度线索。研究多深度线索融合的场景深度估计理论和优化方法，旨在解决现有方法受景深限制深度估计结果精度不高的问题，以及单一线索深度估计结果可靠性缺乏评价依据的问题。具体研究内容包括：1）针对多线索融合的深度估计问题，分析视差深度线索与模糊深度线索的不同特性，寻求将它们融合于一个计算模型的方法。2）针对多线索之间的相互约束问题，研究深度线索间的强弱约束条件及其数学描述。3）针对深度计算结果的可靠性评价问题，探索基于强弱约束的可靠性评价模型以及相应的深度优化方法。本项目属于计算机视觉领域基本理论与方法研究，为增强现实、视觉导航、场景监控、影视特效制作等相关应用提供精确的深度数据，研究成果具有重要的理论意义及应用价值。

中文关键词： 深度估计；摄像机阵列；多深度线索；全局优化；遮挡模型

英文摘要： Recent research progresses of 3D reconstruction in computer vision and visual psychology of human being have indicated that multiple depth cues based depth estimation approach outperforms traditional single cue based ones. The fundamental data of the project are multiple depth cues, which are extracted from multi-view images and synthetic aperture photography based on a dense camera array. The primary objective of the proposed work is to tackle two issues, one is the inaccuracy of depth estimation caused by the limitation of depth of field, and another is lack of evaluation model for depth map derived from single depth cue. So the core idea of the proposed work is depth estimation and optimization for complicated scene by fusing multiple depth cues. We will focus on three important questions that must be addressed in building multiple depth-cue fusion based depth estimation. 1) Aiming at the issue of joint model of depth estimation by fusing multiple cues, we are going to analyze the characteristics of disparity cue and blur cue first, and then we try to find a suitable way to put these cues into a unified model and minimize the objective function via convex optimization algorithm. 2) Aiming at the issue of mutual constraints of multiple depth cues, we propose to model two kinds of constraints among these cues,

英文关键词： Depth estimation；Camera array；Multiple depth cues；Global optimization；Occlusion model