Geometric Inconsistencies Research Articles

Enhanced RGB-D Mapping Method for Detailed 3D Indoor and Outdoor Modeling

RGB-D sensors (sensors with RGB camera and Depth camera) are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks including limited measurement ranges (e.g., within 3 m) and errors in depth measurement increase with distance from the sensor with respect to 3D dense mapping. In this paper, we present a novel approach to geometrically integrate the depth scene and RGB scene to enlarge the measurement distance of RGB-D sensors and enrich the details of model generated from depth images. First, precise calibration for RGB-D Sensors is introduced. In addition to the calibration of internal and external parameters for both, IR camera and RGB camera, the relative pose between RGB camera and IR camera is also calibrated. Second, to ensure poses accuracy of RGB images, a refined false features matches rejection method is introduced by combining the depth information and initial camera poses between frames of the RGB-D sensor. Then, a global optimization model is used to improve the accuracy of the camera pose, decreasing the inconsistencies between the depth frames in advance. In order to eliminate the geometric inconsistencies between RGB scene and depth scene, the scale ambiguity problem encountered during the pose estimation with RGB image sequences can be resolved by integrating the depth and visual information and a robust rigid-transformation recovery method is developed to register RGB scene to depth scene. The benefit of the proposed joint optimization method is firstly evaluated with the publicly available benchmark datasets collected with Kinect. Then, the proposed method is examined by tests with two sets of datasets collected in both outside and inside environments. The experimental results demonstrate the feasibility and robustness of the proposed method.

Rectified unstructured T-splines with dynamic weighted refinement for improvement in geometric consistency and approximation convergence

T-splines developed on unstructured meshes are called unstructured T-splines, which have the problem of geometric inconsistency and unfairness of mesh density evolution over regular or irregular elements during the refinement. Geometric inconsistency means that the geometry defined by an unstructured T-spline keeps changing throughout the refinement. The unfairness of mesh density evolution pertains to different scalings of regular and irregular elements during the refinement, which drags down the convergence of the approximation result in isogeometric analysis. This paper proposes rectified unstructured T-splines to solve these two problems with the dynamic weighted refinement and rectified T-spline basis functions. Owing to the dynamic weighted refinement, the mesh size scaling tends to 12 fairly everywhere on unstructured meshes, and geometric consistency is improved with the rectified T-spline basis functions. The approximation convergence is also greatly enhanced for isogeometric analysis from the original unstructured T-splines, which is quite meaningful for engineering simulations.

Integrated visualization for reinforced concrete using ultrasonic tomography and image-based 3-D reconstruction

A comprehensive visualization scheme to characterize reinforced concrete structures, based on integrated ultrasonic tomography and 3-D computer vision, is presented. A recently developed hybrid air-coupled/contact ultrasonic transducer system enables the generation of internal tomographic images that characterize the interior condition, for example the presence of voiding defects, of full-scale reinforced concrete elements. Based on tomographic cross-sectional slice images, 3-D volumetric internal images are built up to obtain full stereoscopic analysis. An automated image-based 3-D reconstruction technique is applied to the same structure to visualize external condition. Both internal and exterior visualizations of full-scale concrete column are integrated in a single three-dimensional image. The approach is demonstrated on a reinforced concrete column sample that exhibits exterior geometric inconsistency with the original design and also includes controlled internal defects. The experimental results demonstrate that the proposed integrated visualization technique provides holistic characterization of the interior and exterior of the test sample and thus demonstrates great potential for facilitating inspection of existing structures in the field.

Automatic and Accurate Conflation of Different Road-Network Vector Data towards Multi-Modal Navigation

With the rapid improvement of geospatial data acquisition and processing techniques, a variety of geospatial databases from public or private organizations have become available. Quite often, one dataset may be superior to other datasets in one, but not all aspects. In Germany, for instance, there were three major road network vector data, viz. Tele Atlas (which is now “TOMTOM”), NAVTEQ (which is now “here”), and ATKIS. However, none of them was qualified for the purpose of multi-modal navigation (e.g., driving + walking): Tele Atlas and NAVTEQ consist of comprehensive routing-relevant information, but many pedestrian ways are missing; ATKIS covers more pedestrian areas but the road objects are not fully attributed. To satisfy the requirements of multi-modal navigation, an automatic approach has been proposed to conflate different road networks together, which involves five routines: (a) road-network matching between datasets; (b) identification of the pedestrian ways; (c) geometric transformation to eliminate geometric inconsistency; (d) topologic remodeling of the conflated road network; and (e) error checking and correction. The proposed approach demonstrates high performance in a number of large test areas and therefore has been successfully utilized for the real-world data production in the whole region of Germany. As a result, the conflated road network allows the multi-modal navigation of “driving + walking”.

On the Monte Carlo simulation of small-field micro-diamond detectors for megavoltage photon dosimetry

Monte Carlo (MC) calculated detector-specific output correction factors for small photon beam dosimetry are commonly used in clinical practice. The technique, with a geometry description based on manufacturer blueprints, offers certain advantages over experimentally determined values but is not free of weaknesses. Independent MC calculations of output correction factors for a PTW-60019 micro-diamond detector were made using the EGSnrc and PENELOPE systems. Compared with published experimental data the MC results showed substantial disagreement for the smallest field size simulated ( mm). To explain the difference between the two datasets, a detector was imaged with x rays searching for possible anomalies in the detector construction or details not included in the blueprints. A discrepancy between the dimension stated in the blueprints for the active detector area and that estimated from the electrical contact seen in the x-ray image was observed. Calculations were repeated using the estimate of a smaller volume, leading to results in excellent agreement with the experimental data. MC users should become aware of the potential differences between the design blueprints of a detector and its manufacturer production, as they may differ substantially. The constraint is applicable to the simulation of any detector type. Comparison with experimental data should be used to reveal geometrical inconsistencies and details not included in technical drawings, in addition to the well-known QA procedure of detector x-ray imaging.

Comment on “The Late Devonian Variscan suture of the Iberian Massif: A correlation of high-pressure belts in NW and SW Iberia. Tectonophysics 654, 96–100" by R. Fernández and R. Arenas

A vast Variscan nappe spreading from the Allochthonous Complexes of NW Iberia to the Ossa-Morena Zone in SW Iberia has been proposed by Díez Fernández and Arenas (2015), based on the correlation of different outcrops of high-pressure and MORB-type rocks. This interpretation conflicts with well-known geological and geophysical data regarding the SW Iberian Variscides, which point to: i) major kinematic and geometric inconsistencies come up when interpreting the Ossa-Morena Zone as an allochthonous unit, ii) the outcrops of high-pressure and MORB-type rocks belong to two different sutures rather than a single one, and iii) SW Iberia is characterized by transpressional deformation related to a very oblique left-lateral continental collision, while NW Iberia features a rather frontal collision.

Sentinel-1A Product Geolocation Accuracy: Commissioning Phase Results

Sentinel-1A (S1A) is an Earth observation satellite carrying a state-of-the-art Synthetic Aperture Radar (SAR) imaging instrument. It was launched by the European Space Agency (ESA) on 3 April 2014. With the end of the in-orbit commissioning phase having been completed at the end of September 2014, S1A data products are already consistently providing highly accurate geolocation. StripMap (SM) mode products were acquired regularly and tested for geolocation accuracy and consistency during dedicated corner reflector (CR) campaigns. At the completion of this phase, small geometric inconsistencies had been understood and mitigated, with the high quality of the final product geolocation estimates reflecting the mission’s success thus far. This paper describes the measurement campaign, the methods used during geolocation estimation, and presents best estimates of the product Absolute Location Error (ALE) available at the beginning of S1A’s operational phase.

Sensor-Driven Calibration and Co-Registration of Airborne Multisensor LiDAR Data

. In large-area LiDAR mapping projects, surveyors might collect data at different times and with different sensors, creating loosely connected laser point clouds with varying point densities, accuracies, and overlaps. Current LiDAR calibration methodologies refine each point cloud and evaluate the accuracy of each point cloud individually. In the case when a surface model is required, an individual DEM tile is derived from each point cloud separately. This traditional workflow often causes geometric inconsistencies in the transitional zones of neighboring survey areas and introduces difficulties in the mosaicking process of the DEM tiles.In this article, a new methodology for generating geometrically correct laser point clouds—free of blunders and systematic errors—and seamless co-registration of multiple neighboring laser point clouds with minimal ground control input is introduced. Datasets collected at different times and/or with multiple equipment can be geometrically rectified in a fully automated fashion through improved sensor parameters, either simultaneously or sequentially within the same least squares adjustment, resulting in a steady flow of accuracy in the overlap zones. Further, by processing adjacent laser point clouds, it is further shown how this procedure reduces the geometric inconsistencies from, initially, several decimeters to a few centimeters and achieves an absolute accuracy of a few centimeters across all survey blocks, consistently, using just one control point. Building on this unique methodology, a new, simplified process for generating more homogenous and more accurate DEM products is suggested.Résumé. Pour des projets de cartographie LiDAR de grande envergure, les géomètres peuvent recueillir des données à des moments différents et avec des capteurs différents. Ceci produit des nuages de points laser aux liens assez lâches avec des densités de points, des précisions et des chevauchements différents. Les méthodologies actuelles de rectification LiDAR affinent et corrigent chaque nuage de points individuellement, ce qui provoque souvent des incohérences géométriques dans les zones de transition des carreaux de levés topographiques voisins et introduit des difficultés dans la création de mosaïques modèles numériques d’élévation (MNE)«Digital Elevation Model (DEM)».Dans cet article, est introduite une nouvelle méthode de rectification LiDAR, qui permet de joindre des nuages de points laser voisins sans discontinuités avec un minimum de point de référence au sol. Des ensembles de données collectées à des moments différents et/ou avec du matériel différent peuvent être corrigés simultanément ou successivement dans le même ajustement des moindres carrés, résultant en un flux continu de précision dans les zones de chevauchement. Il est en outre montré comment cette procédure réduit les incohérences géométriques et la perte d’information généralement associées avec le processus de création de mosaïques MNE «DEM» traditionnel, et réalise des produits MNE «DEM» plus homogènes, cohérents, et précis.

Making in-Front-of Cars Transparent: Sharing First-Person-Views via Dashcam

Visual obstruction caused by a preceding vehicle is one of the key factors threatening driving safety. One possible solution is to share the first-person-view of the preceding vehicle to unveil the blocked field-of-view of the following vehicle. However, the geometric inconsistency caused by the camera-eye discrepancy renders view sharing between different cars a very challenging task. In this paper, we present a first-person-perspective image rendering algorithm to solve this problem. Firstly, we contour unobstructed view as the transferred region, then by iteratively estimating local homography transformations and performing perspective-adaptive warping using the estimated transformations, we are able to locally adjust the shape of the unobstructed view so that its perspective and boundary could be matched to that of the occluded region. Thus, the composited view is seamless in both the perceived perspective and photometric appearance, creating an impression as if the preceding vehicle is transparent. Our system improves the driver's visibility and thus relieves the burden on the driver, which in turn increases comfort. We demonstrate the usability and stability of our system by performing its evaluation with several challenging data sets collected from real-world driving scenarios.

3P2-K05 球体駆動用小型球形オムニホイール(パラレルロボット・メカニズム)

In our previous work, we proposed a spherical haptic interface which has unlimited workspace. It requires compact omni-directional wheels to drive a sphere. However, the conventional omni-wheel that consists with two wheels has a significant drawback that introduces geometric inconsistency. Recently, the omni-wheel with single wheel was introduced, but it is difficult to make it compact. In this paper, we propose a new omni-directional wheel which is based on "Omni-Ball." It achieves both consistent driving and compact design. A prototype model is designed and developed. In addition, a design approach based on slip property is introduced.

Forensic Image Analysis - A Frame work

Forensic image analysis is the application of image science & domain expertise to interpret the content of an image and/or image itself in legal matters. Regardless, of the type of image analysis performed, forensic experts need to perform mainly three tasks such as image interpretation, image examination and technical preparation in day today activities [2-7]. First, Interpretation is the application of specific subject matter expertise to draw conclusions about subjects or objects depicted in images. Examples include a podiatrist drawing conclusions about foot shape from an image, a shoeprint expert drawing conclusions Abstract The large volume and variety of digital images currently acquired and used in different application domain has given rise to the requirement of image analysis. Images can be found in many application domains such as journalism, advertizing, medicine, weather forecasting, video surveillance, map production, remote sensing, computer aided designs etc. In particular, there is an increasing need for the development of image analysis in the forensic science, to place the perpetrator at the scene of a crime. While each application has requirements unique from the others, all are concerned with faster, cheaper, and more accurate results. Ease with which the images can be created, they may be manipulated to sway opinions or for monetary gains; one needs to be aware that seeing does not always imply believing, especially in courtrooms. And also the human visual system is, at times remarkably inept at detecting simple geometric inconsistencies that might result from photo tempering. Even sometimes, simple differences may not be identified by the visual system. Analysis of images for information extraction has become very prominent area of interest in recent past. This article provides an overview of various issues used for forensic image analysis (FIA) using the three main components: Pre-processing, Feature extraction and the Image analysis. Embedding such capabilities of image analysis components in visual surveillance systems may automatically detect hostile intent in advance.

도심지역의 고해상도 위성영상 정합에 대한 그림자 영향 분석

다중 시기에 수집된 고해상도 위성영상은 효과적인 도심지 분석과 모니터링을 위한 필수적인 자료이다. 그러나 같은 지역에 대해 다른 센서에서 수집된 영상은 물론, 동일 센서 영상이라 하더라도 두 영상간의 기하학적 위치정보가 서로 일치하지 않는 문제가 존재한다. 따라서 다중 영상의 효과적인 활용을 위해서는 영상 정합을 위해 매칭 포인트를 추출하는 일이 필수적이다. 그러나 도심지의 경우 건물, 교량, 나무, 기타 인공 구조물 등의 영향으로 넓은 영역에 그림자가 분포하며 그림자의 방향과 강도는 영상 수집 시기에 따라 달라지기 때문에 정확한 매칭 포인트를 추출하는데 어려움이 있다. 본 연구에서는 대표적인 매칭점 추출 기법인 SIFT(Scale-Invariant Feature Transform) 기법과 자동 그림자 추출 기법을 적용하여 도심지역의 그림자가 영상 정합에 미치는 영향을 분석하였다. 영상 분할을 통해 생성된 세그먼트의 분광 및 공간인자를 이용하여 그림자 객체를 추출하였으며 이 때 건물 버퍼 영역을 그림자의 인접정보로서 활용하였다. SIFT 기법을 통해 추출된 매칭점이 그림자에 위치하는 경우 이를 제거하고 영상 정합을 수행하였다. 최종적으로 고해상도 위성영상의 정합에 대한 그림자의 영향을 분석하기 위해 추출된 매칭점과 정합 결과의 정확도를 정량적, 시각적으로 평가하였다.

Multi-Temporal Time-Dependent Terrain Visualization through Localized Spatial Correspondence Parameterization

Visualizing quantitative time-dependent changes in the topography requires relying on a series of discrete given multi-temporal topographic datasets that were acquired on a given time-line. The reality of physical phenomenon occurring during the acquisition times is complex when trying to mutually model the datasets; thus, different levels of spatial inter-relations and geometric inconsistencies among the datasets exist. Any straight forward simulation will result in a truncated, ill-correct and un-smooth visualization. A desired quantitative and qualitative modelling is presumed to describe morphologic changes that occurred, so it can be utilized to carry out more precise and true-to-nature visualization tasks, while trying to best describe the reality transition as it occurred. This research paper suggests adopting a fully automatic hierarchical modelling mechanism, hence implementing several levels of spatial correspondence between the topographic datasets. This quantification is then utilized for the datasets morphing and blending tasks required for intermediate scene visualization. The establishment of a digital model that stores the local spatial transformation parameterization correspondences between the topographic datasets is realized. Along with designated interpolation concepts, this complete process ensures that the visualized transition from one topographic dataset to the other via the quantified correspondences is smooth and continuous, while maintaining morphological and topological relations.

A new look into the kinematics and dynamics of finite rigid body rotations using Lie group theory

A systematic theoretical approach is presented, in an effort to provide a complete and illuminating study on kinematics and dynamics of rigid bodies rotating about a fixed point. Specifically, this approach is based on some fundamental concepts of differential geometry, with particular reference to Lie group theory. This treatment is motivated by the form of the configuration space corresponding to large rigid body rotation, which is a differentiable manifold possessing group properties. First, the basic steps of the classical approach on the subject are briefly summarized. Then, some geometrical tools are presented, which are essential for supporting and illustrating the steps and findings of the new approach. Finally, the emphasis is placed on a thorough investigation of the problem of finite rotations. A key idea is the introduction of a canonical connection, matching the manifold and group properties of the configuration space. This proves to be sufficient and effective for performing the kinematics. Next, following the selection of an appropriate metric, the dynamics is also carried over. The present approach is theoretically more demanding than the traditional treatments in engineering but brings substantial benefits. In particular, an elegant interpretation is provided for all the quantities with fundamental importance in both rigid body kinematics and dynamics. Most importantly, this also leads to a correction of some misconceptions and geometrical inconsistencies in the field. Among other things, the deeper understanding of the theoretical concepts provides powerful insight and a strong basis for the development of efficient numerical techniques in problems of solid and structural mechanics involving large rotations.

Exposing photo manipulation with inconsistent reflections

The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. In this article we describe a new forensic technique that focuses on geometric inconsistencies that arise when fake reflections are inserted into a photograph or when a photograph containing reflections is manipulated. This analysis employs basic rules of reflective geometry and linear perspective projection, makes minimal assumptions about the scene geometry, and only requires the user to identify corresponding points on an object and its reflection. The analysis is also insensitive to common image editing operations such as resampling, color manipulations, and lossy compression. We demonstrate this technique with both visually plausible forgeries of our own creation and commercially produced forgeries.

Three-dimensional proxies for hand-drawn characters

Drawing shapes by hand and manipulating computer-generated objects are the two dominant forms of animation. Though each medium has its own advantages, the techniques developed for one medium are not easily leveraged in the other medium because hand animation is two-dimensional, and inferring the third dimension is mathematically ambiguous. A second challenge is that the character is a consistent three-dimensional (3D) object in computer animation while hand animators introduce geometric inconsistencies in the two-dimensional (2D) shapes to better convey a character's emotional state and personality. In this work, we identify 3D proxies to connect hand-drawn animation and 3D computer animation. We present an integrated approach to generate three levels of 3D proxies: single-points, polygonal shapes, and a full joint hierarchy. We demonstrate how this approach enables one medium to take advantage of techniques developed for the other; for example, 3D physical simulation is used to create clothes for a hand-animated character, and a traditionally trained animator is able to influence the performance of a 3D character while drawing with paper and pencil.

Precise Geometric Resigtration of Aerial Imagery and LIDAR Data

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

J025021 シート状多細胞組織の形態発生に関する数理モデルの検討([J02502]生命体統合シミュレーション(2))

Three-dimensional (3D) vertex model is one of successful to understand morphogenetic dynamics of multicellular tissue. In particular, a fundamental 3D vertex model to express cellular arrangement in tissue is suggested (H. Honda, J. Theol. Biol. 2004). To our knowledge, there is currently no alternative model in the 3D vertex ones to simulate the arrangement. However the effects of cell and tissue large deformations along with physical and geometrical inconsistencies impede expressing a natural vertex dynamics. In this study, we suggest a novel model in which an artificial drift of morphogenetic dynamics is attenuated, and in which the geometrical inconsistencies are removed.

Detecting conjugate-point pairs for map alignment between two polygon datasets

When the same objects in different datasets have different positions and shapes, map alignment is necessary to minimise these geometric inconsistencies for successful map integration. In this paper, we propose a method to detect conjugate-point pairs for aligning two polygon datasets by matching the contours of corresponding polygons. This method comprises three processes, including identification of the corresponding polygon pairs, shape approximation with virtual corner-vertices and detection of conjugate-point pairs with our modified vertex-attributed-string-matching (VASM) algorithm. We applied this method to two distinct spatial datasets; a cadastral map and a topographical map of the same urban area. Then, the performance of our method was assessed visually and statistically. Both evaluations showed satisfactory results.

An Inter-Landmark Approach to 4-D Shape Extraction and Interpretation: Application to Myocardial Motion Assessment in MRI

This paper presents a novel approach to shape extraction and interpretation in 4-D cardiac magnetic resonance imaging data. Statistical modeling of spatiotemporal interlandmark relationships is performed to enable the decomposition of global shape constraints and subsequently of the image analysis tasks. The introduced descriptors furthermore provide invariance to similarity transformations and thus eliminate pose estimation errors in the presence of image artifacts or geometrical inconsistencies. A set of algorithms are derived to address key technical issues related to constrained boundary tracking, dynamic model relaxation, automatic initialization, and dysfunction localization. The proposed framework is validated with a relatively large dataset of 50 subjects and compared to existing statistical shape modeling methods. The results indicate increased adaptation to spatiotemporal variations and imaging conditions.