返回
Cell-based shape reconstruction from incomplete silhouettes
DOI:10.3233/ICA-180597.png)
摘要
En 中文
Shape reconstruction from images is one of the most widely adopted approaches to compute accurate 3D reconstructions of people or objects in a multi-camera environment. However, such algorithms are traditionally very sensitive to errors in the silhouettes due to imperfect foreground-background estimation or occluding objects appearing between the camera and the object of interest. We propose a novel algorithm that is still able to provide high quality reconstruction from incomplete silhouettes. At the core of the method is the partitioning of the reconstruction space in cells, i.e. regions with uniform camera and silhouette coverage properties. An iterative process is proposed which incrementally adds cells to the temporal reconstruction based on their potential to explain the observed silhouettes from different cameras. Experimental results are close to manually labelled approaches and outperform standard leave-M-out reconstruction techniques in terms of F1-score.
Keyword:
Shape reconstruction
occlusion
multi-camera fusion
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
5.3
论文数:
491
被引数:
735
机构
引用论文
Time‐Varying Latent Effect Model for Longitudinal Data with Informative Observation Times
Biometrics
IF0
Object Occlusion Detection Using Automatic Camera Calibration for a Wide-Area Video Surveillance System用于广域视频监控系统的使用自动摄像机校准的对象遮挡检测
SENSORS
IF3.5

