An interface for sketching 3D curves

Conventional interactive 3D tree modeling systems are generally based on 2D input devices, and it's not convenient to generate desired 3D tree shape from 2D inputs due to the complexity of 3D tree structures. In this paper, we present a system for modeling trees interactively using a 3D gesture-based VR platform. The system contains a head-mounted display (HMD) and a 6-DOF motion controller for interaction. We propose an improved procedural modeling method to generate trees faster for VR platform. Using the 6-DOF motion controller, users can manipulate tree structures by a set of 3D interactive operations, including geometric editing using 3D gestures, sketching, brushing and silhouette-guided growth. Our interactions are more flexible and convenient than using traditional 2D input devices, e.g., we allow the user to simultaneously rotate and translate parts of a tree using a 3D gesture.

BackgroundAortic shape has been proposed as an important determinant of adverse haemodynamics following coarctation repair. However, previous studies have not demonstrated a consistent relationship between shape and vascular load. In this study, 3D aortic shape was evaluated using principal component analysis (PCA), allowing investigation of the relationship between 3D shape and haemodynamics.MethodsSixty subjects (38 male, 25.0 ± 7.8 years) with repaired coarctation were recruited. Central aortic haemodynamics including wave intensity analysis were measured noninvasively using a combination of blood pressure and phase contrast cardiovascular magnetic resonance (CMR). 3D curvature and radius data were derived from CMR angiograms. PCA was separately performed on 3D radius and curvature data to assess the role of arch geometry on haemodynamics. Clinical findings were corroborated using 1D vascular models.ResultsThere were no independent associations between 3D curvature and any hemodynamic parameters. However, the magnitude of the backwards compression wave was related to the 1st (r = − 0.36, p = 0.005), 3rd (r = 0.27, p = 0.036) and 4th (r = − 0.31, p = 0.017) principle components of radius. The 4th principle componentof radius also correlated with central aortic systolic pressure. These aortas had larger aortic roots, more transverse arch hypoplasia and narrower aortic isthmuses.ConclusionsThere are major modes of variation in 3D aortic shape after coarctation repair witha modest association between variation in aortic radius and pathological wave reflections, but not with 3D curvature. Taken together, these data suggest that shape is not the major determinant of vascular load following coarctation repair, and calibre is more important than curvature.

Article Virtual world modeler Share on Authors: Elton K. H. Tsang Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong KongView Profile , Hanqiu Sun Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong KongView Profile , Mark Green Department of Computer Science, University of Alberta, Canada Department of Computer Science, University of Alberta, CanadaView Profile Authors Info & Claims VRST '98: Proceedings of the ACM symposium on Virtual reality software and technologyNovember 1998 Pages 179–186https://doi.org/10.1145/293701.293734Online:02 November 1998Publication History 3citation432DownloadsMetricsTotal Citations3Total Downloads432Last 12 Months4Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Time-Dependent Density-Functional Theory (TDDFT) has become a promising alternative to the Bethe-Salpeter Equation (BSE) in terms of the calculation of optical spectra, including excitoinic features, due to its significantly lower computational cost. TDDFT brings with it the advantage of, in principle, access to the Time-Dependent (TD) exciton wave function and the ability to study ultra-fast TD phenomena. One promising family of Exchange & Correlation (XC) functionals for capturing excitonic effects in TDDFT are the Long-Range Corrected (LRC) functionals. In order to test the LRC functionals, we have written programs to do calculations in both a One-Dimensional (1D) and Two-Dimensional (2D) model systems. We used the 1D model system to explore avenues of TD exciton wave function visualization to facilitate the study and understanding of the TD dynamics of excitons. Likewise, we used the 2D model system to study various methods of correction to the LRC in hopes of better capturing excitonic effects and improving stability for Real-Time (RT) calculations. We show examples of exciton wave functions visualized with various techniques, including waterfall plots and heat maps. We have also used our 1D model system to explore how RT calculations performed using TDDFT can be used to gain insight into novel systems, as exemplified by our study of charge-transfer excitations. Using our 2D model system we have explored two possible avenues of correction to the LRC: adding a 'counter' term to the XC functional and 'generalizing' the differential equation which defines the LRC. The first avenue we explored is the addition of a new term to the XC potential, explicitly constructed to cancel out the error produced by the LRC's violation of the zero-force theorem, leading to the introduction of spurious, nonphysical, internal forces. This approach, in the end, does not seem to make a substantial impact on the optical absorption spectra or the stability of the LRC. The second avenue, using the so-called "Proca" equation, adds terms to the equation of motion in order to stabilize the calculations-again with limited success. We have successfully demonstrated in our model systems that the RT methods for TDDFT are promising tools for the exploration of TD phenomena in electronic systems. We have also explored these techniques using some illustrative situations and avenues for improving the accuracy and stability of these calculations.

A new technique is proposed for calibrating a 3D modeling system with variable zoom based on multi-view stereo image analysis. The 3D modeling system uses a stereo camera with variable zoom setting and a turntable for rotating an object. Given an object whose complete 3D model (mesh and texture-map) needs to be generated, the object is placed on the turntable and stereo images of the object are captured from multiple views by rotating the turntable. Partial 3D models generated from different views are integrated to obtain a complete 3D model of the object. Changing the zoom to accommodate objects of different sizes and at different distances from the stereo camera changes several internal camera parameters such as focal length and image center. Also, the parameters of the rotation axis of the turntable changes. We present camera calibration techniques for estimating the camera parameters and the rotation axis for different zoom settings. The Perspective Projection Matrices (PPM) of the cameras are calibrated at a selected set of zoom settings. The PPM is decomposed into intrinsic parameters, orientation angles, and translation vectors. Camera parameters at an arbitrary intermediate zoom setting are estimated from the nearest calibrated zoom positions through interpolation. A performance evaluation of this technique is presented with experimental results. We also present a refinement technique for stereo rectification that improves partial shape recovery. And the rotation axis of multi-view at different zoom setting is estimated without further calibration. Complete 3D models obtained with our techniques are presented.

In this paper, we demonstrate a 3D object modeling system utilizing a setup which consists of two CMOS cameras and a DLP projector by making use of structured light and stereo vision. The calibration of the system is carried out using calibration pattern. The images are taken with stereo camera pair by projecting structured light onto the object and the correspondence problem is solved by both epipolar constraint of stereo vision and gray code constraint of structured light. The first experimental results show that the proposed 3D modeling system is able to model the object successfully.

Generative modeling is an approach to computer-assisted geometric modeling. The goal of the approach is to allow convenient and high-level specification of shapes, and provide tools for rendering and analysis of the specified shapes. Shapes include curves, surfaces, and solids in 3D space, as well as higher-dimensional entities such as surfaces deforming in time, and solids with a spatially varying mass density. Shape specification in the approach involves combining low-dimensional entities, especially 2D curves, into higher-dimensional shapes. This combination is specified through a powerful shape description language which builds multidimensional parametric functions. The language is based on a set of primitive operators on parametric functions which include arithmetic operators, vector and matrix operators, integration and differentiation, constraint solution and global optimization. Although each primitive operator is fairly simple, high-level shapes and shape building operators can be defined using recursive combination of the primitive operators. The approach encourages the modeler to build parameterized families of shapes rather than single instances. Shapes can be parameterized by scalar parameters (e.g., time or joint angle) or higher-dimensional parameters (e.g., a curve controlling how the scale of a cross section varies as it is translated). Such parameterized shapes allow easy modification of the design, since the modeler can interact with parameters that relate to high-level properties of the shape. In contrast, many geometric modeling systems use a much lower-level specification, such as through sets of many 3D control points. Tools for rendering and analysis of generative models are developed using the concept of interval analysis. Each primitive operator on parametric functions has an inclusion function method, which produces an interval bound on the range of the function, given an interval bound on its domain. With these inclusion functions, robust algorithms exist for computing solutions to nonlinear systems of constraints and global minimization problems, when these problems are expressed in the modeling language. These algorithms, in turn, are developed into robust approximation techniques to compute intersections, CSG operations, and offset operations.

The visual hull is used to 3D object modeling in real-time. In this paper, we propose a novel method to remove phantom volumes produced in the polyhedral visual hull (PVH) construction. This method calculates the visual hull by using polygon intersection. By making full use of the information PVH supplied for image planes, we finally obtain the safe polyhedral visual hull (SPVH). Unlike the method based image method, according to the construction process of the PVH, this paper presents a fast ray-volume intersection based on geometry method. Experiment results show that, without adding more cameras, this method can provide view-independent SPVH model with phantom volumes removed, which can be used in the 3D modeling and interactive system.

The similarity relation for the line of ideal isothermal compressibility for 2D systems in liquid state

Mechanical circulatory support emerged for the pediatric population in the late 1980s as a bridge to cardiac transplantation. The Total Artificial Heart (TAH-t) (SynCardia Systems Inc., Tuscon, AZ) has been approved for compassionate use by the Food and Drug Administration for patients with end-stage biventricular heart failure as a bridge to heart transplantation since 1985 and has had FDA approval since 2004. However, of the 1,061 patients placed on the TAH-t, only 21 (2%) were under the age 18. SynCardia Systems, Inc. recommends a minimum patient body surface area (BSA) of 1.7 m(2), thus, limiting pediatric application of this device. This unique case report shares this pediatric institution's first experience with the TAH-t. A 14-year-old male was admitted with dilated cardiomyopathy and severe biventricular heart failure. The patient rapidly decompensated, requiring extracorporeal life support. An echocardiogram revealed severe biventricular dysfunction and diffuse clot formation in the left ventricle and outflow tract. The decision was made to transition to biventricular assist device. The biventricular failure and clot formation helped guide the team to the TAH-t, in spite of a BSA (1.5 m(2)) below the recommendation of 1.7 m(2). A computed tomography (CT) scan of the thorax, in conjunction with a novel three-dimensional (3D) modeling system and team, assisted in determining appropriate fit. Chest CT and 3D modeling following implantation were utilized to determine all major vascular structures were unobstructed and the bronchi were open. The virtual 3D model confirmed appropriate device fit with no evidence of compression to the left pulmonary veins. The postoperative course was complicated by a left lung opacification. The left lung anomalies proved to be atelectasis and improved with aggressive recruitment maneuvers. The patient was supported for 11 days prior to transplantation. Chest CT and 3D modeling were crucial in assessing whether the device would fit, as well as postoperative complications in this smaller pediatric patient.

Three-dimensional human face modeling is a very popular topic with many applications,such as facial animation, face recognition and model-based facial video communication. Therefore, how to model the facial geometry, texture intensity and illumination variation is important in computer vision and graphics. Previous works on 3D head modeling from a single face image utilized prior information on 3D head models. However, it is difficult to accurately reconstruct the 3D face model from a single face image with expression since the facial expression induces 3D face model deformation in a complex manner. The main challenge is the coupling of the neutral 3D face model and the 3D deformation due to expression, thus making the 3D model estimation from a single face image with expression very challenging. On the other hand, the illumination condition also makes the problem more difficult. In this thesis,we focus on developing a 3D face model reconstruction system including surface registration and training of 3D face models with expressional deformations as well as the estimation of the 3D neutral shape and the 3D expressional deformation from a single face image. The proposed reconstruction algorithm integrates the linear and non-linear subspace representations for a prior 3D neutral morphable model and the probabilistic manifold-based 3D expressional deformation. We incorporate the face geometry, expression deformation, texture and illumination information into the problem so that it is well constrained. The reconstructed 3D face models can also be further extended and applied to many real-world applications.

The most time-consuming part of character animation is 3D character posing. Posing using a mouse is a slow and tedious task that involves sequences of selecting on-screen control handles and manipulating the handles to adjust character parameters, such as joint rotations and end effector positions. Thus, various 3D user interfaces have been proposed to make animating easier, but they typically provide less accuracy. The proposed interface combines a mouse with the Leap Motion device to provide 3D input. A usability study showed that users preferred the Leap Motion over a mouse as a 3D gestural input device. The Leap Motion drastically decreased the number of required operations and the task completion time, especially for novice users.

A 3D surface modeling system for intelligent excavation system

Image-based 3D shape reconstruction is essential for 3D modeling in recognition, virtual reality, generation of video games, 3D animation, and in the creation of 3D virtual fitting rooms - the sought-after application in this dissertation. In this work, we propose a novel reconstruction method that uses a generic 3D model that roughly controls the overall reconstruction shape which in turn, reduces the number of 2D images needed to just two (frontal and profile) for obtaining a 3D point model. The generic model consists of a massive set of 3D points that lack saliency, topological meaning, and relational interconnections. This is also true about points in the two canonical images. In this work, we propose finding a small set of interconnected ordered intrinsic salient points (control points) residing on the silhouette of the projections of the generic model onto the two image spaces, as well as finding those for the canonical images. Points on the generic model and the images are automatically given saliency with order and interconnections through loop-subdivision operating on those control points and their equivalent points on the canonical images. The transformation of the generic model into the specific object is done through morphing the points on the generic model to follow and be consistent with their equivalent points on the canonical images. The control points on the canonical images are automatically obtained using an active shape model (ASM) that modifies an average trained control point set attained using an offline training, to account for class shape variability and boundary regularization guaranteeing the control points to reside on the silhouette (boundary) of the individual. The reconstructed 3D model is furtherly refined through smoothing the reconstructed surface, while fixing local holes using a principle component analysis (PCA) decomposition. This reconstruction method is convenient, simple, efficient, and results in an average geometric error of less than 0.5% over 700 diverse body models from the CAESAR dataset. We then implement the contour-based articulated model to the personalized 3D model for pose recovery. The evolution of the model through the articulation process is captured in a video clip. 3D transformations are found and applied to the 3D model on its parts so that the projections of the 3D model 'match' those observed in the video sequence at corresponding frames. This is done by minimizing the error between the frontal projection body region points and the target points from the image for each independent moving part, with sub-resolution recovery errors. Once the personalized 3D model is obtained and the articulated model is implemented, the algorithm simulates how garments virtually appear on the reconstructed person under different poses. Different types of clothes are classified as tight or loose, where for the first type of garments, the garment is mapped onto the person's body, whereas for the second type, the mapping adjusts to accommodate the loose nature of the garment, and its fitting on the body of the reconstructed person model. This creates a virtual in-home fitting room for garment fitting, which is timely and is a needed application that would go hand in hand with online clothes shopping, allowing the trying of garments at home with changing poses before ordering them, and can be updated as often as necessary to accommodate changes in physique, weight, aging, etc. This is also done with minimum requirements from the user aside from taking two images and a video of pose articulations using their cam or smart phone, and stands as a useful, needed, and attractive App.

Patellofemoral pain (PFP) is suggested as a precursor of patellofemoral osteoarthritis (PFOA) later in life. This hypothesis is based on shared risk factors for both diseases, such as deviating alignment parameters. In patients with PFOA, certain 2D alignment parameters and 3D shape variations are associated with the progression of PFOA. The relationship among alignment, shape, and PFP persistence remains unclear to date. To investigate the association between 2D alignment parameters, 3D bone shape variations, and PFP persistence. Questionnaire and magnetic resonance imaging (MRI) data from 64 patients between 14 and 40 years of age with PFP were selected from a case-control study. Participants who completed follow-up questionnaires at one or two years of follow-up were included. PFP persistence, measured using a 7-point Likert scale, was dichotomized. Structural abnormalities were scored using the MRI Osteoarthritis Knee Score (MOAKS), and alignment parameters were determined following standardized methods. The patellae were segmented from the MRI using a semi-automatic segmentation algorithm, and a 3D statistical shape model was created. Shape modes explaining at least 1% of total population variation were included. Regression analyses were performed to determine the association among baseline function (anterior knee pain scale (AKPS)), MOAKS features, alignment parameters, 3D patellar shape modes, and PFP persistence. Fifty-five participants completed follow-up questionnaires and were included in the current analyses. Participants had a mean (standard deviation) age of 23.2 (6.8), and 58.2% were female. AKPS increased statistically significantly from 65.7 (10.6) at baseline to 75.9 (14.9) at follow-up. Nineteen patellar shape modes were included in the analyses, of which four showed a P-value <0.05; however, they were not statistically significant after applying Bonferroni correction. No associations were found among MOAKS, alignment parameters, shape modes, and PFP persistence in the adjusted models. Only AKPS at baseline was associated with pain severity at follow-up (β​=​-0.13, 95% confidence interval: -0.20; -0.07). No statistically significant associations were found among structural abnormalities, 2D alignment, or 3D shape modes, and PFP persistence. Only worse AKPS at baseline was associated with persistent PFP, suggesting that baseline function might be a better predictor than structural abnormalities, alignment, or bone shape. III.