An algorithm for computing extrinsic camera parameters for far-range photogrammetry based on essential matrix

2010 ◽  
Author(s):  
Huimin Cai ◽  
Kejie Li ◽  
Meilian Liu
2021 ◽  
Vol 11 (5) ◽  
pp. 2033
Author(s):  
Sangguk Cha ◽  
Da-Yoon Nam ◽  
Jong-Ki Han

Virtual reality (VR) has been one of the most important topics in the field of multimedia signals and systems for approximately 10 years [...]


2009 ◽  
Vol 26 (2) ◽  
pp. 200-214 ◽  
Author(s):  
Jiuxiang Hu ◽  
Anshuman Razdan ◽  
Joseph A. Zehnder

Abstract A technique for calibrating digital cameras for stereo photogrammetry of cumulus clouds is presented. It has been applied to characterize the formation of summer thunderstorms observed during the Cumulus Photogrammetric, In Situ, and Doppler Observations (CuPIDO) project. Starting from gross measurements of locations, orientations of cameras, and landmark surveys, accurate locations and orientations of the cameras are obtained by minimizing a geometric error (GE). Once accurate camera parameters are obtained, 3D positions of cloud-feature points are computed by triangulation. The main contributions of this paper are as follows. First, it is proven that the GE has only one minimum in the neighborhood of the real parameters of a camera. In other words, searching the minimum of the GE enables the authors to find the right camera parameters even if there are significant differences between the initial measurements and their true values. Second, a new coarse-to-fine iterative algorithm is developed that minimizes the GE and finds the camera parameters. Numerical experiments show that the coarse-to-fine algorithm is efficient and effective. Third, a new landmark survey based on a geographic information system (GIS) rather than field measurements is presented. The GIS landmark survey is an effective and efficient way to obtain landmark world coordinates for camera calibrations in these experiments. Validation of this technique is achieved by the data collected by a NASA/Earth Observing System satellite and an instrumented aircraft. This paper builds on previous research and details the calibration and 3D reconstructions.


PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1801 ◽  
Author(s):  
Robin S.S. Kramer

Background.In recent years, researchers have investigated the relationship between facial width-to-height ratio (FWHR) and a variety of threat and dominance behaviours. The majority of methods involved measuring FWHR from 2D photographs of faces. However, individuals can vary dramatically in their appearance across images, which poses an obvious problem for reliable FWHR measurement.Methods.I compared the effect sizes due to the differences between images taken with unconstrained camera parameters (Studies 1 and 2) or varied facial expressions (Study 3) to the effect size due to identity, i.e., the differences between people. In Study 1, images of Hollywood actors were collected from film screenshots, providing the least amount of experimental control. In Study 2, controlled photographs, which only varied in focal length and distance to camera, were analysed. In Study 3, images of different facial expressions, taken in controlled conditions, were measured.Results.Analyses revealed that simply varying the focal length and distance between the camera and face had a relatively small effect on FWHR, and therefore may prove less of a problem if uncontrolled in study designs. In contrast, when all camera parameters (including the camera itself) are allowed to vary, the effect size due to identity was greater than the effect of image selection, but the ranking of the identities was significantly altered by the particular image used. Finally, I found significant changes to FWHR when people posed with four of seven emotional expressions in comparison with neutral, and the effect size due to expression was larger than differences due to identity.Discussion.The results of these three studies demonstrate that even when head pose is limited to forward facing, changes to the camera parameters and a person’s facial expression have sizable effects on FWHR measurement. Therefore, analysing images that fail to constrain some of these variables can lead to noisy and unreliable results, but also relationships caused by previously unconsidered confounds.


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