A point-cloud-based multiview stereo algorithm for free-viewpoint video
Related Experiment Video
Updated: May 31, 2026

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
Published on: December 5, 2013
Yebin Liu1, Qionghai Dai, Wenli Xu
1Tsinghua University, Beijing, People's Republic of China. liuyebin@tsinghua.edu.cn
Abstract:
This paper presents a robust multiview stereo (MVS) algorithm for free-viewpoint video. Our MVS scheme is totally point-cloud-based and consists of three stages: point cloud extraction, merging, and meshing. To guarantee reconstruction accuracy, point clouds are first extracted according to a stereo matching metric which is robust to noise, occlusion, and lack of texture. Visual hull information, frontier points, and implicit points are then detected and fused with point fidelity information in the merging and meshing steps. All aspects of our method are designed to counteract potential challenges in MVS data sets for accurate and complete model reconstruction. Experimental results demonstrate that our technique produces the most competitive performance among current algorithms under sparse viewpoint setups according to both static and motion MVS data sets.
More Related Videos
Related Concept Videos
Three-Dimensional Force System:Problem Solving
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
One-Degree-of-Freedom System
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
Deconvolution
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Depth Perception and Spatial Vision
Uniform Depth Channel Flow
Uniform Depth Channel Flow: Problem Solving

