Camera Arrangement using Geometric Optimization to Minimize Localization Error in Stereo-vision Systems

H. Kamali Ardakani; Seyed A. Mousavinia; F. Safaei

Volume 9, Issue 3 , July 2021, , Pages 295-307

http://dx.doi.org/10.22044/jadm.2021.9855.2117

Abstract
  Stereo machine vision can be used as a Space Sampling technique and the cameras parameters and configuration can effectively change the number of Samples in each Volume of space called Space Sampling Density (SSD). Using the concept of Voxels, this paper presents a method to optimize the geometric configuration ...  Read More

H.6.5.2. Computer vision
Camera Arrangement in Visual 3D Systems using Iso-disparity Model to Enhance Depth Estimation Accuracy

M. Karami; A. Moosavie nia; M. Ehsanian

Volume 8, Issue 1 , January 2020, , Pages 1-12

http://dx.doi.org/10.22044/jadm.2019.7209.1855

Abstract
  In this paper we address the problem of automatic arrangement of cameras in a 3D system to enhance the performance of depth acquisition procedure. Lacking ground truth or a priori information, a measure of uncertainty is required to assess the quality of reconstruction. The mathematical model of iso-disparity ...  Read More

H.3.2.2. Computer vision
Depth Improvement for FTV Systems Based on the Gradual Omission of Outliers

H. Hosseinpour; Seyed A. Moosavie nia; M. A. Pourmina

Volume 7, Issue 4 , November 2019, , Pages 563-574

http://dx.doi.org/10.22044/jadm.2019.7278.1864

Abstract
  Virtual view synthesis is an essential part of computer vision and 3D applications. A high-quality depth map is the main problem with virtual view synthesis. Because as compared to the color image the resolution of the corresponding depth image is low. In this paper, an efficient and confided method ...  Read More