Browsing by Subject "RMS errors"

Now showing 1 - 2 of 2

Open Access
A color-based face tracking algorithm for enhancing interaction with mobile devices
(Springer, 2010-05) Bulbul, A.; Cipiloglu, Z.; Capin, T.
A color-based face tracking algorithm is proposed to be used as a human-computer interaction tool on mobile devices. The solution provides a natural means of interaction enabling a motion parallax effect in applications. The algorithm considers the characteristics of mobile useconstrained computational resources and varying environmental conditions. The solution is based on color comparisons and works on images gathered from the front camera of a device. In addition to color comparisons, the coherency of the facial pixels is considered in the algorithm. Several applications are also demonstrated in this work, which use the face position to determine the viewpoint in a virtual scene, or for browsing large images. The accuracy of the system is tested under different environmental conditions such as lighting and background, and the performance of the system is measured in different types of mobile devices. According to these measurements the system allows for accurate (7% RMS error) face tracking in real time (20-100 fps). © Springer-Verlag 2010.
Open Access
Optimization of F2 layer parameters using IRI-Plas model and IONOLAB Total Electron Content
(IEEE, 2011) Sahin O.; Sezen, U.; Arikan F.; Arıkan, Orhan; Aktug, B.
In this study, the relation of the maximum ionization height (HmF2) and the critical frequency (FoF2) of F2 layer is examined within their parametric range through the International Reference Ionosphere extended towards the plasmasphere (IRI-Plas) model and the IONOLAB-TEC (Total Electron Content) observations. HmF2 and FoF2 are optimized using an iterational loop through Non-Linear Least Squares method by also using a physical relation constraint between these two parameters. Performance evaluation of optimization algorithm is performed separately for the cases running IRI-Plas with optimized parameters and TEC input; only with optimized parameters; only with TEC and finally with no optimized parameter and TEC input. As a conclusion, it is seen that using optimized parameters and TEC together as input produces best IRI-TEC estimates. But also using only optimized parameters (without TEC update) gives estimates with also very low RMS errors and is suitable to use in optimizations. HmF2 and FoF2 estimates are obtained separately for a quiet day, positively corrupted day, negatively corrupted day, a northern latitude and a southern latitude. HmF2 and FoF2 estimation results are compared with ionosonde data where available. This study enables the modification and update of empirical and deterministic IRI Model to include instantaneous variability of the ionosphere. © 2011 IEEE.