The new cascaded shape regression architecture proposed in this paper is actually an algorithm by Component Adaptive Mechanism (CAM) to cope with unconstrained face alignment. CAM divides the process ...of face alignment into two parts: the updating process of face box and the cascaded shape regression process by Component Adaptive Mechanism. The former process first adjusts face box by training different classifiers to estimate its transformation parameters and thereby outputs more accurate initialized shape. The latter process uses Component Adaptive Mechanism to fuse results of different domain-specific regressors to further update the shape. The major innovation of CAM is characterized by its fault-tolerated mechanism which is shown in the following two aspects. (1) A probability-based fern classifier is adopted in the partition of the optimization space into multiple domains of homogeneous descent, which not only endows the algorithm with the fault-tolerance mechanism but also augments the available training set of each domain. (2) A training strategy based on dominant set approach is used to train a stronger domain-specific regressor by dynamically adjusting the weight of objective function corresponding to different shapes and therefore regressors derived from the training are equipped with fault-tolerance ability. Conducted on such public image datasets as AFLW-full (19-pts), COFW (29-pts) and 300-W (68-pts), experiments show that the proposed CAM: (1) can deal with the problem of face detection and face alignment simultaneously; (2) is superior to existing algorithms in solving face alignment problems with extreme variations in pose, expression, illumination and partial occlusion.
Multimodal image registration is critical yet challenging for remote sensing image processing. Due to the large nonlinear intensity differences between the multimodal images, conventional search ...algorithms tend to get trapped into local optima when optimizing the transformation parameters by maximizing mutual information (MI). To address this problem, inspired by transfer learning, we propose a novel search algorithm named transfer optimization (TO), which can be applied to any optimizer. In TO, an optimizer transfers its better individuals to the other optimizer in each iteration. Thus, TO can share information between two optimizers and take advantage of their search mechanisms, which is helpful to avoid the local optima. Then, the registration of the multimodal remote sensing images using TO is presented. We compare the proposed algorithm with several state-of-the-art algorithms on real and simulated image pairs. Experimental results demonstrate the superiority of our algorithm in terms of registration accuracy.
The increasing demand for 3D geospatial data is driving the development of new products. Laser scanners are becoming more mobile, affordable, and user-friendly. With the increased number of systems ...and service providers on the market, the scope of mobile laser scanning (MLS) applications has expanded dramatically in recent years. However, quality control measures are not keeping pace with the flood of data. Evaluating MLS surveys of long corridors with control points is expensive and, as a result, is frequently neglected. However, information on data quality is crucial, particularly for safety-critical tasks in infrastructure engineering. In this paper, we propose an efficient method for the quality control of MLS point clouds. Based on point cloud discrepancies, we estimate the transformation parameters profile-wise. The elegance of the approach lies in its ability to detect and correct small, high-frequency errors. To demonstrate its potential, we apply the method to real-world data collected with two high-end, car-mounted MLSs. The field study revealed tremendous systematic variations of two passes following tunnels, varied co-registration quality of two scanners, and local inhomogeneities due to poor positioning quality. In each case, the method succeeds in mitigating errors and thus in enhancing quality.
With strong technology improvement, especially GNSS, coordinate transformation has become an essential tool in everyday practice. For this reason, it is beneficial to have a good understanding of the ...mathematical process of coordinate transformation, as well as the method for calculating transformation parameters. The purpose of this article is to provide a detailed explanation of the coordinate transformation procedure and the calculation of transformation parameters for seven transformation models: 3-parameter, 5-parameter standard and abridged, 7-parameter, 8-parameter, 9-parameter, and 12-parameter. For each transformation model, a basic transformation equation, a procedure for calculating transformation parameters, inverse expression for reversible transformation, as well as characteristics of each model are provided. As an addition, for each model, a numerical example of calculating transformation parameters for the territory of the Republic of Croatia is provided. Additionally, for the example of the 7-parameter transformation, importance of reversible transformation, rotation convention, as well as the form of the rotation matrix used during transformation are demonstrated.
ITRF (International Terrestrial Reference Frame) determines the origin, alignment of the system ’s fundamental planes or axes, scale, physical constants, and models such as the size, shape, and ...alignment of the reference ellipsoid. The ITRF is regularly updated to take into account the Earth’s dynamics and is now sufficiently re-fined to ensure that the change between successive ITRF versions is in the order of 1-2 cm. The Egyptian Survey Authority (ESA) established the Egyptian’s HARN (High Accuracy Reference Network) and linked it to the international frame (ITRF1994 epoch1996) as a static frame. As this datum is static, coordinates of stations do not change with time, ignoring both the tectonic motion and the different definitions for all following ITRF realizations.
With the continuous increasing progress of using the IGS and CORS stations as well as the merging of the concept of tectonic plate motion, and the Precise Point Positioning technique has a well know precise technique, there were offset in the current coordinates of the HARN network about 40 cm, so a set of simple transformation parameters (T
, T
, T
) calculated.
In the current study, Plate Motion Models (PPM) and Egyptian Deformation Model (EGY-DM) were investigated based on ITRF2008 epoch2015.4 to choose the best model in calculating the computed parameters.
The evaluation process of the computed transformation parameters on chosen points of HARN & NACN (Notational Agricultural Cadastral network) demonstrates that the estimated transformation parameters by EGY-DM give the lowest horizontal and vertical differences 16 mm and 17mm, respectively, and with standard deviation does not exceed 2 cm, except one station due to deficiency of observation time.
Previous studies have not evaluated the systematic errors implied in the third generation of BeiDou-3 Navigation Satellite System (BDS-3) broadcast ephemeris. In this paper we evaluate the systematic ...pattern described by the Helmert transformation parameters, including translations, rotations, and scale. BDS-3 broadcast and precise ephemerides from December 2019 to 2022 are collected, and the characteristics of the transformation parameters as well as their effects on the signal in space error are analysed. The annual variation in the z-translation is obtained, and the similar amplitudes of 5.5 cm and phases of approximate 300 days are obtained for different years. When the rotation parameters are considered in the orbit comparison, the Root Mean Square (RMS) errors of the along- and cross-track orbital differences decrease from 29.1 to 12.5 cm and from 30.6 to 9.2 cm, respectively, because the three rotation parameters compensate for the majority of the errors in the BDS-3 broadcast ephemeris. Moreover, the high correlations in the obtained rotation parameters among the three orbital planes suggest that the orientation of the BDS-3 broadcast ephemeris is influenced by common model errors, i.e., uncertainty of Earth Rotation Parameters (ERPs). Further research is required because an offset of 1.5 × 10
–9
for the scale parameter is observed. A degraded User Range Error (URE) for epochs of up to 84% is attained when the systematic pattern is considered, though the impact of the systematic pattern indicated by the z-translation and rotation parameters on the URE is less than 5.0 cm. With the refinement of the ERPs implemented in the new generation of broadcast ephemeris, we anticipate that the broadcast ephemeris performance of BDS-3 will be improved.
Accuracy of 3D geodetic coordinates transformed from one coordinate system to another is analysed. Values of transformation parameters are computed by least-squares adjustment method. Accuracy of ...transformation parameters and points 3D coordinates transformed into a new coordinate system is determined by taking into account accuracy of identical points in both coordinate systems. Known formulas of transformation parameters for accuracy evaluation are taking into account only the accuracy of new system identical points coordinates. It is determined that 3D coordinates transformed into a new system accuracy is less than the accuracy of coordinates in the old one. Formulas for estimating transformation parameters and covariance of transformed 3D coordinates matrixes are given and derived for adjusted parameter vector values computation and their covariance matrix determination. Article in Lithuanian Erdvinių geodezinių koordinačių transformavimo algoritmu tikslumas Santrauka. Straipsnyje analizuojamas erdvinių geodezinių koordinačių, gautų transformuojant jas iš vienos koordinačių sistemos į kitą, tikslumas. Transformavimo parametrų reikšmės apskaičiuojamos mažiausiųjų kvadratų metodu. Transformavimo parametrų bei transformuotų į naująją koordinačių sistemą taškų erdvinių koordinačių tikslumas nustatomas atsižvelgiant į identiškų taškų koordinačių abiejose sistemose tikslumą. Ligšiolinėse egzistuojančiose transformavimo parametrų tikslumo įvertinimo formulėse atsižvelgiama tik į naujosios sistemos identiškų taškų koordinačių tikslumą. Nustatyta, kad į naująją sistemą transformuotų erdvinių koordinačių tikslumas yra mažesnis už senosios sistemos koordinačių tikslumą. Pateikiamos formulės transformavimo parametrų ir transformuotų erdvinių koordinačių kovariacijų matricoms bei jų įverčiams skaičiuoti. Raktažodžiai: transformavimo parametrai, kovariacija.
The accuracy of the coordinates computed by transformation from one system to another is analysed. Values of transformation parameters are computed by the least-square method taking into account the ...accuracy of the coordinates of the identical points in both coordinate systems. Thus the accuracy of the transformed coordinates is analysed taking into account the influence both of the coefficients of the transformation equations and the errors of transformation parameters. Covariance matrix of the transformed coordinates is combined from two components. One component estimates the influence of the coefficients of the transformation equations, and the second one - the influence of errors of transformation parameters. The formulas for computing the covariance matrix of the transformed coordinates is presented. Article in Lithuanian Plokštuminių ir erdvinių geodezinių koordinačių transformavimo algoritmų tikslumo analizė Santrauka. Nagrinėjamas geodezinių koordinačių, transformuojamų iš vienos koordinačių sistemos į kitą, tikslumas. Transformavimo parametrų reikšmės apskaičiuojamos mažiausiųjų kvadratų metodu, atsižvelgiant į identiškų taškų abiejose koordinačių sistemose tikslumą. Transformuotų į naują sistemą koordinačių tikslumas analizuojamas įvertinant transformavimo lygčių koeficientų bei transformavimo parametrų klaidų įtaką. Transformuotų koordinačių kovariacijų matrica sudaroma iš dviejų komponenčių. Viena komponentė įvertina transformavimo lygčių koeficientų klaidų įtaką, o antroji – transformavimo parametrų klaidų įtaką transformuotų koordinačių tikslumui. Pateikiamos formulės transformuotų koordinačių kovariacijų matricoms skaičiuoti. Prasminiai žodžiai: transformavimo parametrai, kovariacijų matrica.
Accuracy of geodetic coordinates transformed from one coordinate system to another is analysed in the publication. Values for transformation parameters are computed using the least-squares method. ...Accuracy of transformation parameters and transformed coordinates is determined by identical points accuracy in both systems. Influence of additional parameters, used for coordinate systematic errors elimination, accuracy of coordinate transformation parameters and transformed coordinates is analysed. Formulas for evaluating matrices on the transformation parameters and coordinate covariance are presented. Article in Lithuanian Geodezinių koordinačių transformavimo Helmerto algoritmu tikslumas Santrauka. Straipsnyje nagrinėjamas geodezinių koordinačių tikslumas, transformuojant jas iš vienos koordinačių sistemos į kitą. Transformavimo parametrų reikšmės apskaičiuojamos mažiausiųjų kvadratų metodu. Transformavimo parametrų bei transformuotų koordinačių tikslumas nustatomas atsižvelgiant į identiškų taškų abiejose koordinačių sistemose tikslumą. Analizuojama papildomų parametrų, taikomų koordinačių sisteminėms klaidoms eliminuoti, įtaka koordinačių transformavimo parametrų bei transformuotų koordinačių tikslumui. Pateikiamos formulės transformavimo parametrų ir transformuotų koordinačių kovariacijų matricoms įvertinti. Raktažodžiai: transformavimo parametrai, kovariacija.
The noise characteristics of the Global Navigation Satellite System (GNSS) position time series can be biased by many factors, which in turn affect the estimates of parameters in the deterministic ...model using a least squares method. The authors assess the effects of seasonal signals, weight matrix, intermittent offsets, and Helmert transformation parameters on the noise analyses. Different solutions are obtained using the simulated and real position time series of 647 global stations and power law noise derived from the residuals of stacking solutions are compared. Since the true noise in the position time series is not available except for the simulated data, the authors paid most attention to the noise difference caused by the variable factors. First, parameterization of seasonal signals in the time series can reduce the colored noise and cause the spectral indexes to be closer to zero (much “whiter”). Meanwhile, the additional offset parameters can also change the colored noise to be much “whiter” and more offsets parameters in the deterministic model leading to spectral indexes closer to zero. Second, the weight matrices derived from the covariance information can induce more colored noise than the unit weight matrix for both real and simulated data, and larger biases of annual amplitude of simulated data are attributed to the covariance information. Third, the Helmert transformation parameters (three translation, three rotation, and one scale) considered in the model show the largest impacts on the power law noise (medians of 0.4 mm−k/4 and 0.06 for the amplitude and spectral index, respectively). Finally, the transformation parameters and full-weight matrix used together in the stacking model can induce different patterns for the horizontal and vertical components, respectively, which are related to different dominant factors.
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