一种新颖的基于品种的3DTV内容生成方案,用于随机捕获的稀疏图片集

Mansi Sharma, S. Chaudhury, Brejesh Lall
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引用次数: 0

摘要

本文提出了一种新的基于参数化多样性的三维探索模型,以理解稀疏的非结构化照片集合,并通过有趣的视点自动规划虚拟的世界地标三维之旅,而无需显式的三维重建。该系统分析了包含相同位置或环境的非结构化但相关的图像数据集合,以创建参数化场景图:一种传达空间关系的数据结构,并使照片之间能够顺利进行虚拟导航。提出了一种新的统计启发式准则,利用场景空间布局和外观来自动识别照片之间的最佳可用门户。一旦连接良好,图形将被参数化并持续渲染,选择视觉上引人注目的3D过渡路径,保持令人愉悦的视差本质。该系统的能力在几张随意拍摄的遗产地个人照片集和从“Flickr”数据收集的图像上得到了证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel variety-based 3DTV content generation scheme for casually captured sparse photo collections
This paper presents a novel parameterized variety-based 3D exploration model to comprehend the sparse unstructured collection of photographs, and automatically plan virtual 3D tours of the world's landmarks through interesting viewpoints without explicit 3D reconstruction. The proposed system analyzes the collection of unstructured but related image data containing the same location or environment to create a parameterized scene graph: a data structure that conveys spatial relations and enable smooth virtual navigation between photos. A novel statistical-heuristic criteria is evolved exploiting the scene spatial layout and appearance to automatically identify best available portals between photographs. Once well connected, the graph is parameterized and consistently rendered choosing visually compelling 3D transition paths, maintaining a pleasing essence of parallax. The system's ability is demonstrated on several casually captured personal photo collections of heritage sites and imagery gathered from “Flickr” data.
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