Homologous Points Research Articles

Разработка и апробация «Российской базы Нейтральных и Улыбающихся женских лиц (“RuNeS Faces”)»

The article presents a database of women’s faces for research in the field of social perception. Each of 55 models was photographed full-face under four conditions: with a neutral or smiling face with hair up or down. The database includes the results of facial morphometry (relative positions of homologous points), expert ratings of appearance style, scores of perceived intelligence and attractiveness. The peculiarity of the database is that, unlike the others, we preserved the natural style featured on the models: clothes, jewelry, and makeup. The database was approbated in the study of physiognomic and appearance style predictors of perceived intelligence and attractiveness. It expands the variety of stimulus images available for researchers and can be used in different studies of social perception.

IMPLEMENTATION OF A REAL-TIME STACKING ALGORITHM IN A PHOTOGRAMMETRIC DIGITAL CAMERA FOR UAVS

Abstract. In the recent years, unmanned aerial vehicles (UAVs) have become an interesting tool in aerial photography and photogrammetry activities. In this context, some applications (like cloudy sky surveys, narrow-spectral imagery and night-vision imagery) need a longexposure time where one of the main problems is the motion blur caused by the erratic camera movements during image acquisition. This paper describes an automatic real-time stacking algorithm which produces a high photogrammetric quality final composite image with an equivalent long-exposure time using several images acquired with short-exposure times. Our method is inspired by feature-based image registration technique. The algorithm is implemented on the light-weight IGN camera, which has an IMU sensor and a SoC/FPGA. To obtain the correct parameters for the resampling of images, the presented method accurately estimates the geometrical relation between the first and the Nth image, taking into account the internal parameters and the distortion of the camera. Features are detected in the first image by the FAST detector, than homologous points on other images are obtained by template matching aided by the IMU sensors. The SoC/FPGA in the camera is used to speed up time-consuming parts of the algorithm such as features detection and images resampling in order to achieve a real-time performance as we want to write only the resulting final image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images, as well as block diagrams of the described architecture. The resulting stacked image obtained on real surveys doesn’t seem visually impaired. Timing results demonstrate that our algorithm can be used in real-time since its processing time is less than the writing time of an image in the storage device. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real-time the gyrometers of the IMU.

Characterization of the age-dependent shape of the pediatric thoracic spine and vertebrae using generalized procrustes analysis.

Generalized Procrustes Analysis (GPA) is a superimposition method used to generate size-invariant distributions of homologous landmark points. Several studies have used GPA to assess the three-dimensional (3D) shapes of or to evaluate sex-related differences in the human brain, skull, rib cage, pelvis and lower limbs. Previous studies of the pediatric thoracic vertebrae suggest that they may undergo changes in shape asa result of normative growth. This study uses GPA and second order polynomial equations to model growth and age- and sex-related changes in shape of the pediatric thoracic spine. We present a thorough analysis of the normative 3D shape, size, and orientation of the pediatric thoracic spine and vertebrae as well as equations which can be used to generate models of the thoracic spine and vertebrae for any age between 1 and 19years. Such models could be used to create more accurate 3D reconstructions of the thoracic spine, generate improved age-specific geometries for finite element models (FEMs) and used to assist clinicians with patient-specific planning and surgical interventions for spine deformity.

Fast and Easy 3D Reconstruction with the Help of Geometric Constraints and Genetic Algorithms

The purpose of the work presented in this paper is to describe new method of 3D reconstruction from one or more uncalibrated images. This method is based on two important concepts: geometric constraints and genetic algorithms (GAs). At first, we are going to discuss the combination between bundle adjustment and GAs that we have proposed in order to improve 3D reconstruction efficiency and success. We used GAs in order to improve fitness quality of initial values that are used in the optimization problem. It will increase surely convergence rate. Extracted geometric constraints are used first to obtain an estimated value of focal length that helps us in the initialization step. Matching homologous points and constraints is used to estimate the 3D model. In fact, our new method gives us a lot of advantages: reducing the estimated parameter number in optimization step, decreasing used image number, winning time and stabilizing good quality of 3D results. At the end, without any prior information about our 3D scene, we obtain an accurate calibration of the cameras, and a realistic 3D model that strictly respects the geometric constraints defined before in an easy way. Various data and examples will be used to highlight the efficiency and competitiveness of our present approach.

ACCURATE REGISTRATION OF THE CHANG’E-1 IIM DATA BASED ON LRO LROC-WAC MOSICA DATA

Abstract. In the detection of the moon, the visible and near-infrared reflectance data of the lunar material are important information sources for lunar chemical substances and mineral inversion. The Interferometer Imaging Spectrometer (IIM) aboard the Chang'E-1 lunar orbiter is the first multispectral imaging spectrometer for Chinese lunar missions. In this paper, we use the mosaic image of global moon acquired by the Wide-angle Camera (WAC) of the Lunar Reconnaissance Orbiter Camera (LROC) to realize the accurate registration of Chang'E-1 IIM hyperspectral images. Due to the lack of GCPs, the emphasis of this work is to find a huge number of homologous points. The method proposed in this paper is to obtain several homologous points by manually matching, and then we utilize those points to calculate the initial homography matrix of LROC-WAC image and IIM image. This matrix is used to predict the area on IIM image where homologous points may be located, and the locations of the homologous points are determined by the orientation correlation in frequency domain. Finally we save the parts of homologous points which satisfied the conversion relationship of initial homography matrix to calculate homography matrix again. We use this iterative way to obtain a more accurate location of the homologous points. In this process, we take into account that the geometric deformations of different regions on IIM image are quite different. Therefore, we added image threshold segmentation based on the initial homography matrix in the experiment, and completed the above work of finding the homologous points on the segmented images. The final realization of registration accuracy of IIM images are in 1–2 pixels (RMSE). This provides a reliable data assurance for the subsequent study of using IIM images to inverse the lunar elements.

Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

Scaling of the reinforcement of soil slopes by living plants in a geotechnical centrifuge

Understanding root-reinforcement of vegetated slopes is hindered by the cost and practicality of full scale tests to explore global behaviour at the slope scale, and the idealised nature of smaller-scale testing to date that has relied on model root analogues. In this study we investigated the potential to use living plant roots in small scale experiments of slope failure that would use a geotechnical centrifuge to achieve soil stress states comparable to those in the field at homologous points. Three species (Willow, Gorse and Festulolium grass), corresponding to distinct plant groups with different root architecture and ‘woodiness’ were selected and cultivated for short periods (2 months for Willow and Festulolium grass, 3 months for Gorse). The morphologies, tensile strength and Young’s modulus of these juvenile root samples and their effects on increasing soil shear strength were then measured (via tensile tests and direct shear tests) and compared with published results of more mature field grown specimens. Our test results show that when all juvenile root samples of the three species are considered, the commonly used negative power law does not fit the data for the relationship between root tensile strength and root diameter well, resulting in very low R2 values (R2<0.14). No significant differences in tensile strength were observed between roots with different diameter for Willow and Gorse, and the average root tensile strength for all juvenile root samples was 8.70±0.60MPa (Mean±SE), 9.50±0.40MPa, 21.67±1.29MPa for Willow, Festulolium grass and Gorse, respectively. However, a strong linear relationship was observed between tensile strength and Young’s modulus of the roots of the juvenile plants (R2=0.55, 0.69, 0.50 for Willow, Festulolium grass and Gorse, respectively). From a centrifuge modelling perspective, it was shown that using juvenile plants could potentially produce prototype root systems that are highly representative of corresponding mature root systems both in terms of root mechanical properties and root morphology when a suitable growing time (2 months) and scaling factor (N=15) are selected. However, it remains a challenge to simultaneously simulate the distribution of root biomass with depth of the corresponding mature plant. Therefore, a compromise has to made to resolve the conflicts between the scaling of rooting depth and root reinforcement, and it is suggested that 1:15 scale would represent a suitable compromise for studying slope failure in a geotechnical centrifuge.

The matching method for veins images

BackgroundA common problem in medical practice is the localization of subcutaneous veins and arteries. Automatization of this procedure may help to develop bloodbot rigs and improve use of image guided surgery. MethodIt is not necessary to have a full 3D model in order to determine their location by calculating the spatial coordinates of veins axes in the adopted coordinate system. A much better solution is pre-segmentation, which provides veins axes, and further search for stereo correspondence in the segmented images. The computational complexity of this approach is much smaller, which ensures its quick operation. A disparity map necessary for the calculation of spatial coordinates is created according to the principle that the most likely correct distance between homologous elements is the minimum distance value. To increase the effectiveness of the method, the difference in the distance between the homologous points and their neighbours is further analysed. ResultsThe method is illustrated with examples of the authors' own images of subcutaneous veins as well as standard images used for the evaluation of new methods for seeking stereo correspondence. In addition, the method has been compared with three recognized and widely used algorithms for matching images. The effectiveness of the new method reaches 100% of properly matched pixels. The largest percentage of mismatches is 27%. The lowest value of standard deviation is 0.1 and the highest 10 pixels. The proposed method is at least two times faster than other presented methods.

A TIE POINT MATCHING STRATEGY FOR VERY HIGH RESOLUTION SAR-OPTICAL STEREOGRAMMETY OVER URBAN AREAS

Abstract. This paper presents a matching strategy for sparsely distributed tie points, which can be used to carry out SAR-optical stereogrammetry. Since matching homologue points in heterogeneous multi-sensor image of complex terrain remains a challenging task, the proposed procedure combines the tie point matching step with the estimation of the corresponding 3D object coordinates. The results of this study are two-fold: On the one hand, they show that fully automatic SAR-optical stereogrammetry using very high resolution data of urban scenes is generally feasible and can provide 3D accuracies in the meter-domain. On the other hand, they highlight the difficulty of multi-sensor image matching, as well as the importance of robust matching strategies.

Parallel image registration method for snapshot Fourier transform imaging spectroscopy

A fast and precise registration method for multi-image snapshot Fourier transform imaging spectroscopy is proposed. This method accomplishes registration of an image array using the positional relationship between homologous points in the subimages, which are obtained offline by preregistration. Through the preregistration process, the registration problem is converted to the problem of using a registration matrix to interpolate subimages. Therefore, the hardware interpolation of graphics processing unit (GPU) texture memory, which has speed advantages for its parallel computing, can be used to significantly enhance computational efficiency. Compared to a central processing unit, GPU performance showed ∼ 27 times acceleration in registration efficiency.

Internet Photogrammetry for Inspection of Seaports

Abstract This paper intends to point out the possibility of using Internet photogrammetry to construct 3D models from the images obtained by means of UAVs (Unmanned Aerial Vehicles). The solutions may be useful for the inspection of ports as to the content of cargo, transport safety or the assessment of the technical infrastructure of port and quays. The solution can be a complement to measurements made by using laser scanning and traditional surveying methods. In this paper the authors recommend a solution useful for creating 3D models from images acquired by the UAV using non-metric images from digital cameras. The developed algorithms, created and presented software allows to generate 3D models through the Internet in two modes: anaglyph and display in shutter systems. The problem of 3D image generation in photogrammetry is solved by using epipolar images. The appropriate method was presented by Kreiling in 1976. However, it applies to photogrammetric images for which the internal orientation is known. In the case of digital images obtained with non-metric cameras it is required to use another solution based on the fundamental matrix concept, introduced by Luong in 1992. In order to determine the matrix which defines the relationship between left and right digital image it is required to have at least eight homologous points. To determine the solution it is necessary to use the SVD (singular value decomposition). By using the fundamental matrix the epipolar lines are determined, which makes the correct orientation of images making stereo pairs, possible. The appropriate mathematical bases and illustrations are included in the publication.

A GEOMETRICAL SIMILARITY PATTERN AS AN EXPERIMENTAL MODEL FOR SHAPES IN ARCHITECTURAL HERITAGE: A CASE STUDY OF THE BASE OF THE PILLARS IN THE CATHEDRAL OF SEVILLE AND THE CHURCH OF SANTIAGO IN JEREZ, SPAIN

Abstract. This paper proposes a procedure for the search of a geometrical similarity pattern in architectural heritage by means of calculating probability indexes to support hypotheses initially endorsed by documentary sources. The buildings analysed are the Cathedral of Seville and the Church of Santiago, in Jerez, Spain. The 3D models of their selected pillars are obtained by means of Terrestrial Laser Scanning (TLS), Optical Scanning (OS) and photogrammetry through image-based modelling software (SFM-IBM). To this end, a procedure for the comparison of shapes is established. It is based on similarity statistics, the determination of homologous points and the agreement of characteristic sections. Here, two key aspects are considered: on the one hand, the metric standpoint; on the other hand, historical-graphical features of the 3D models: composition, techniques, styles, and historical-graphical documentary sources. Thus, putting aside the mere dimensional analysis, the sections are compared with graphical patterns and models of which the same authorship – stonemasons working in that age – is accurately known. As a result, the outcomes of this research reveal the geometrical similarity between the elements of the pillars of the Cathedral of Seville and the Church of Santiago.

Global robust image rotation from combined weighted averaging

In this paper we present a novel rotation averaging scheme as part of our global image orientation model. This model is based on homologous points in overlapping images and is robust against outliers. It is applicable to various kinds of image data and provides accurate initializations for a subsequent bundle adjustment. The computation of global rotations is a combined optimization scheme: First, rotations are estimated in a convex relaxed semidefinite program. Rotations are required to be in the convex hull of the rotation group SO(3), which in most cases leads to correct rotations. Second, the estimation is improved in an iterative least squares optimization in the Lie algebra of SO(3). In order to deal with outliers in the relative rotations, we developed a sequential graph optimization algorithm that is able to detect and eliminate incorrect rotations. From the beginning, we propagate covariance information which allows for a weighting in the least squares estimation. We evaluate our approach using both synthetic and real image datasets. Compared to recent state-of-the-art rotation averaging and global image orientation algorithms, our proposed scheme reaches a high degree of robustness and accuracy. Moreover, it is also applicable to large Internet datasets, which shows its efficiency.

An automatic co-registration approach for optical and SAR data in urban areas

ABSTRACTWith the increasing applications of multisource remote sensing, the synergistic use of optical and Synthetic Aperture Radar (SAR) remote sensing images is becoming increasingly popular. Although numerous approaches have been proposed to register satellite images between two optical images or between two SAR images, these approaches cannot be directly applied to register optical and SAR images due to the differences of imaging mechanism between optical and SAR remote sensing. Therefore, the co-registration between optical and SAR images remains challenging, especially in urban areas where surface geometric configuration is much more complex. This study aims to propose a fast and automatic approach for optical and SAR data co-registration based on an assumption of affine transformation between the two images. With a set of initial homologous points generated automatically, an optimization is applied towards the initial homologous points on the SAR images subject to an affine transformation model and a given threshold of root mean square errors (RMSEs) for the co-registration. Three various data sets of optical and SAR images, including SPOT-5 and ENVISAT ASAR, Landsat TM and ENVISAT ASAR, and SPOT-5 and ALOS PALSAR, were employed to test and validate the effectiveness of the proposed method. Experimental results demonstrate the promising effectiveness of the proposed approach with a significant reduction of RMSE compared with the initial homologous points. The proposed approach is especially applicable in urban areas where the uncertain errors of homologous points in SAR images are higher due to the speckles and foreshortening, layover and shadows from tall buildings.

An Improved Image Registration Based on Nonsubsampled Contourlet Transform and Zernike Moments

Feature-based registration is an effective and most widely used image registration method currently. It includes three critical steps, feature extraction, feature matching and transformation parameters estimation. This paper mainly explores the first two steps. In one of Chahira Serief’s paper about image registration, feature points extraction based on nonsubsampled contourlet transform (NSCT) was proposed and feature points matching based on Zernike moments was adopted. The registration accuracy and robustness of his algorithm are acceptable, but it can still be improved. In this paper, an improved scheme of this registration algorithm is proposed. The rotation invariance of NSCT-based feature points extraction is improved, which is beneficial to extract homologous feature points. And the reliability and effectiveness of Zernike momentsbased feature points matching are improved, which can improve the matching accuracy. The improved registration algorithm can realize registration of images related by larger scaling, rotation and translation transformation. The simulation results show that the registration robustness is further improved, and the registration accuracy is still high.

Analysis of the Fitting Accuracy of the 3d Affine Transformation Applied to Cartosat-1 (IRS P5) Satellite Stereo Imagery

Since few years ago it has been generally accepted without any dispute that the 3D affine transformation applied to high-resolution satellite imageries (HRSI), produces results as accurate as those obtained by the RPCs derived from rigorous photogrammetric model. However, as the higher order terms are absent in the affine transformation, the degree of success of this model obviously hinges upon the geometric nature of the imagery to be geo-rectified. In authors view, there are a latent confusion and misunderstanding in the minds of the photogrammetric practitioners as regards the potential of the 3D affine transformation as a replacement model for the geometric correction of the HRSI. The main intention of this paper is, therefore, to analyse the 3D affine transformation by concentrating more on its limitations. To obtain deeper insight into the nature of the 3D affine model, it is applied to images with larger field of view as well as the images of highly mountainous terrains. The geo-coding success of the affine model is then evaluated by comparing the object coordinates of a dense cloud of homologous points derived by the affine model with the object coordinates of the same points obtained by the standard terrain-independent rational functions. Extensive tests conducted over excessively mountainous as well as the hilly terrains indicate that there are clear distortion trends in the residual ground coordinates that cannot be fully absorbed into the 3D affine coefficients. The sources of these non-linear trends such as the satellite attitude and position variations, the terrain relief, the earth curvature and their impact on the final accuracy are analysed using the scatter patterns of the residual errors.

EVALUATION OF METHODS FOR COREGISTRATION AND FUSION OF RPAS-BASED 3D POINT CLOUDS AND THERMAL INFRARED IMAGES

This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

EVALUATION OF METHODS FOR COREGISTRATION AND FUSION OF RPAS-BASED 3D POINT CLOUDS AND THERMAL INFRARED IMAGES

Abstract. This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR) images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i) coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii) coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii) coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv) coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v) coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

POSITIONAL ACCURACY ASSESSMENT OF THE OPENSTREETMAP BUILDINGS LAYER THROUGH AUTOMATIC HOMOLOGOUS PAIRS DETECTION: THE METHOD AND A CASE STUDY

OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data. Being OSM increasingly exploited in a variety of applications, research has placed great attention on the assessment of its quality. This work focuses on assessing the quality of OSM buildings. While most of the studies available in literature are limited to the evaluation of OSM building completeness, this work proposes an original approach to assess the positional accuracy of OSM buildings based on comparison with a reference dataset. The comparison relies on a quasi-automated detection of homologous pairs on the two datasets. Based on the homologous pairs found, warping algorithms like e.g. affine transformations and multi-resolution splines can be applied to the OSM buildings to generate a new version having an optimal local match to the reference layer. A quality assessment of the OSM buildings of Milan Municipality (Northern Italy), having an area of about 180 km2, is then presented. After computing some measures of completeness, the algorithm based on homologous points is run using the building layer of the official vector cartography of Milan Municipality as the reference dataset. Approximately 100000 homologous points are found, which show a systematic translation of about 0.4 m on both the X and Y directions and a mean distance of about 0.8 m between the datasets. Besides its efficiency and high degree of automation, the algorithm generates a warped version of OSM buildings which, having by definition a closest match to the reference buildings, can be eventually integrated in the OSM database.

POSITIONAL ACCURACY ASSESSMENT OF THE OPENSTREETMAP BUILDINGS LAYER THROUGH AUTOMATIC HOMOLOGOUS PAIRS DETECTION: THE METHOD AND A CASE STUDY

Abstract. OpenStreetMap (OSM) is currently the largest openly licensed collection of geospatial data. Being OSM increasingly exploited in a variety of applications, research has placed great attention on the assessment of its quality. This work focuses on assessing the quality of OSM buildings. While most of the studies available in literature are limited to the evaluation of OSM building completeness, this work proposes an original approach to assess the positional accuracy of OSM buildings based on comparison with a reference dataset. The comparison relies on a quasi-automated detection of homologous pairs on the two datasets. Based on the homologous pairs found, warping algorithms like e.g. affine transformations and multi-resolution splines can be applied to the OSM buildings to generate a new version having an optimal local match to the reference layer. A quality assessment of the OSM buildings of Milan Municipality (Northern Italy), having an area of about 180 km2, is then presented. After computing some measures of completeness, the algorithm based on homologous points is run using the building layer of the official vector cartography of Milan Municipality as the reference dataset. Approximately 100000 homologous points are found, which show a systematic translation of about 0.4 m on both the X and Y directions and a mean distance of about 0.8 m between the datasets. Besides its efficiency and high degree of automation, the algorithm generates a warped version of OSM buildings which, having by definition a closest match to the reference buildings, can be eventually integrated in the OSM database.