Real-time Geometry Research Articles

Real‐Time Ray Tracing of Micro‐Poly Geometry with Hierarchical Level of Detail

AbstractIn recent work, Nanite has demonstrated how to rasterize virtualized micro‐poly geometry in real time, thus enabling immense geometric complexity. We present a system that employs similar methods for real‐time ray tracing of micro‐poly geometry. The geometry is preprocessed in almost the same fashion: Nearby triangles are clustered together and clusters get merged and simplified to obtain hierarchical level of detail (LOD). Then these clusters are compressed and stored in a GPU‐friendly data structure. At run time, Nanite selects relevant clusters, decompresses them and immediately rasterizes them. Instead of rasterization, we decompress each selected cluster into a small bounding volume hierarchy (BVH) in the format expected by the ray tracing hardware. Then we build a complete BVH on top of the bounding volumes of these clusters and use it for ray tracing. Our BVH build reaches more than 74% of the attainable peak memory bandwidth and thus it can be done per frame. Since LOD selection happens per frame at the granularity of clusters, all triangles cover a small area in screen space.

An Online Data Visualization Feedback Protocol for Motor Imagery-Based BCI Training.

Brain–computer interface (BCI) has developed rapidly over the past two decades, mainly due to advancements in machine learning. Subjects must learn to modulate their brain activities to ensure a successful BCI. Feedback training is a practical approach to this learning process; however, the commonly used classifier-dependent approaches have inherent limitations such as the need for calibration and a lack of continuous feedback over long periods of time. This paper proposes an online data visualization feedback protocol that intuitively reflects the EEG distribution in Riemannian geometry in real time. Rather than learning a hyperplane, the Riemannian geometry formulation allows iterative learning of prototypical covariance matrices that are translated into visualized feedback through diffusion map process. Ten subjects were recruited for MI-BCI (motor imagery-BCI) training experiments. The subjects learned to modulate their sensorimotor rhythm to centralize the points within one category and to separate points belonging to different categories. The results show favorable overall training effects in terms of the class distinctiveness and EEG feature discriminancy over a 3-day training with 30% learners. A steadily increased class distinctiveness in the last three sessions suggests that the advanced training protocol is effective. The optimal frequency band was consistent during the 3-day training, and the difference between subjects with good or low MI-BCI performance could be clearly observed. We believe that the proposed feedback protocol has promising application prospect.

Physics driven real-time blood flow simulations

Predictive modeling of blood flow and pressure have numerous applications ranging from non-invasive assessment of functional significance of disease to planning invasive procedures. While several such predictive modeling techniques have been proposed, their use in the clinic has been limited due in part to the significant time required to perform virtual interventions and compute the resultant changes in hemodynamic conditions. We propose a fast hemodynamic assessment method to aid in interventional planning based on first constructing an exploration space of geometries, tailored to each patient, and subsequently building a physics driven reduced order model in this space. We demonstrate that this method can predict fractional flow reserve derived from coronary computed tomography angiography in response to changes to a patient-specific lumen geometry in real time while achieving high accuracy when compared to computational fluid dynamics simulations. We validated this method on over 1300 patients that received a coronary CT scan and demonstrated a correlation coefficient of 0.98 with an error of 0.005±0.015 (95% CI: (-0.020, 0.031)) as compared to three-dimensional blood flow calculations. This technology is implemented in a product that has received clearance by the U.S. Food and Drug Administration and is being used clinically to enable physicians to predict changes in blood flow resulting from removal of coronary stenoses as might occur with percutaneous coronary interventions. This technology is also cleared for use in Japan and pending regulatory approval in Europe.

Using Impedance Planimetry (EndoFLIP) to Evaluate Myotomy and Predict Outcomes After Surgery for Achalasia

BackgroundThe functional lumen imaging probe (FLIP) is an innovative tool that uses impedance planimetry to assess esophageal geometry in real time. It has been used to diagnose achalasia and evaluate treatment failure after laparoscopic Heller myotomy (LHM) and peroral endoscopic myotomy (POEM). We hypothesize that impedance planimetry can be utilized intra-operatively to assess adequacy of myotomy and assist in predicting patient outcomes. MethodsA prospectively maintained patient database at a single center was queried. Seventy-seven patients with achalasia underwent POEM or LHM by a single surgeon. The FLIP was used to measure cross-sectional area (CSA), minimum diameter (Dmin), balloon pressure, and distensibility index (DI) of the lower esophageal sphincter (LES) before and after the procedure. Clinical outcomes were measured up to 2 years after treatment. ResultsPost-operative CSA, Dmin, balloon pressure, and DI values were significantly different from pre-operative values (p < 0.001). Patients with a post-operative Eckardt score ≥ 3 were significantly more likely to have a final DI ≤ 3.1 mm2/mmHg (p = 0.014) or a change in DI ≤ 3.0 mm2/mmHg (p = 0.010). Additionally, a final CSA > 96 mm2 or Dmin > 11.0mm was predictive of worse reflux at 2 years (p = 0.01). ConclusionImpedance planimetry using the FLIP can offer intra-operative feedback about the geometry of the LES. The most useful parameters in predicting patient outcomes have yet to be clearly defined, but our results demonstrate that final DI and CSA are predictive of post-operative treatment response.

Noncontact speckle contrast diffuse correlation tomography of blood flow distributions in tissues with arbitrary geometries.

A noncontact electron multiplying charge-coupled-device (EMCCD)-based speckle contrast diffuse correlation tomography (scDCT) technology has been recently developed in our laboratory, allowing for noninvasive three-dimensional measurement of tissue blood flow distributions. One major remaining constraint in the scDCT is the assumption of a semi-infinite tissue volume with a flat surface, which affects the image reconstruction accuracy for tissues with irregular geometries. An advanced photometric stereo technique (PST) was integrated into the scDCT system to obtain the surface geometry in real time for image reconstruction. Computer simulations demonstrated that a priori knowledge of tissue surface geometry is crucial for precisely reconstructing the anomaly with blood flow contrast. Importantly, the innovative integration design with one single-EMCCD camera for both PST and scDCT data collection obviates the need for offline alignment of sources and detectors on the tissue boundary. The in vivo imaging capability of the updated scDCT is demonstrated by imaging dynamic changes in forearm blood flow distribution during a cuff-occlusion procedure. The feasibility and safety in clinical use are evidenced by intraoperative imaging of mastectomy skin flaps and comparison with fluorescence angiography.

Display in the Wild (DIW): An Adaptive Projection-Imaging System to Screen Geometry in Real Time

TVs and monitors are among the most widely used displays in various environments. However, they have limitations in their physical display conditions, such as a fixed size/position and a rigid/flat space. In this paper, we suggest a new “Display in the Wild” (DIW) concept to overcome the aforementioned problems. Our proposed DIW system allows us to display a flexibly large screen on dynamic non-planar surfaces at an arbitrary display position. To implement our DIW concept practically, we choose a projector as the hardware configuration in order to generate a screen anywhere with different sizes. However, distortion occurs when the projector displays content on a surface that is dynamic and/or non-planar. Therefore, we propose a distortion correction method for DIW to overcome the aforementioned surface constraints. Since projectors are not capture devices, we propose using a depth camera to determine the distortions on the surfaces quickly. We also propose DIW-specific calibration and fast/precise correction methods. Our calibration method is constructed to detect the projection surface easily and quickly, and also allows our proposed system to accommodate the intrinsic parameters such as a display resolution and field of view. We accomplish a fast undistortion process of the projector by considering only surface boundary pixels, which enables our method to run in real time. In our comprehensive experiments, the proposed DIW system generates undistorted screens such as TVs and monitors on dynamic non-planar surfaces at an arbitrary display position with Unmanned Aerial Vehicles (UAVs) in a fast and accurate manner, demonstrating its usefulness in practical DIW scenarios.

A feedforward controller for tuning laser cladding melt pool geometry in real time

In this paper, a feedforward proportional-integral (PI) controller is developed to effectively control and tune the laser cladding melt pool geometry in real time. Width setpoint is included in the computer numerically controlled (CNC) programming, making possible its instantaneous change in relation to the position and time, as opposed to conventional controllers that do not have real-time information about these variables. The new concept of variable setpoint at different positions applied to laser cladding represents a great improvement in its use for changeable geometry applications such as blade fabrication. Several experiments are performed to characterize the behaviour of the system, revealing some key factors from monitoring system and image processing crucial for the controller. Laser power is selected as the input control variable, and the clad width is chosen as the output. The width of the melt pool is obtained based on measurements of CMOS camera images and an in-house image processing software algorithm. Closed-loop parameters are identified from the experimental data and Matlab simulations. The architecture of the controller consists on a conventional PI feedback loop and a feedforward module that shows low overshoot and fast response times. Instantaneous connections between laser, CNC, and PC systems allow for knowing the relationship among the exact position and real and setpoint melt pool values. The performance of the controller is verified in the fabrication of cladded parts with variable widths and in real time.

Real‐time inversions for finite fault slip models and rupture geometry based on high‐rate GPS data

We present an inversion strategy capable of using real‐time high‐rate GPS data to simultaneously solve for a distributed slip model and fault geometry in real time as a rupture unfolds. We employ Bayesian inference to find the optimal fault geometry and the distribution of possible slip models for that geometry using a simple analytical solution. By adopting an analytical Bayesian approach, we can solve this complex inversion problem (including calculating the uncertainties on our results) in real time. Furthermore, since the joint inversion for distributed slip and fault geometry can be computed in real time, the time required to obtain a source model of the earthquake does not depend on the computational cost. Instead, the time required is controlled by the duration of the rupture and the time required for information to propagate from the source to the receivers. We apply our modeling approach, called Bayesian Evidence‐based Fault Orientation and Real‐time Earthquake Slip, to the 2011 Tohoku‐oki earthquake, 2003 Tokachi‐oki earthquake, and a simulated Hayward fault earthquake. In all three cases, the inversion recovers the magnitude, spatial distribution of slip, and fault geometry in real time. Since our inversion relies on static offsets estimated from real‐time high‐rate GPS data, we also present performance tests of various approaches to estimating quasi‐static offsets in real time. We find that the raw high‐rate time series are the best data to use for determining the moment magnitude of the event, but slightly smoothing the raw time series helps stabilize the inversion for fault geometry.

Visualization of dynamic keyhole behavior in waveform-controlled plasma arc welding

To overcome the shortcomings of conventional plasma arc welding (PAW), the “controlled pulse keyholing” strategy is proposed and the waveform-controlled keyhole PAW system is developed. To deeply understand the dynamic behaviors of keyhole in this novel PAW process, it is essential to measure and monitor the dynamic variation information of the keyhole geometry in real time. In this study, a vision system is developed to acquire the images of the keyhole from the underside of the workpiece. When a fully penetrated keyhole (open keyhole) is formed, clear keyhole images are captured. Both CCD camera and an efflux plasma voltage sensor are used to measure and characterize the keyhole shape and size during the waveform-controlled PAW process. The dynamic variation features of keyhole shape in a pulse cycle are visualized. The phenomena of “one keyhole in each pulse” and periodic partial-open keyhole transformation are experimentally sensed. The observation results lay solid foundation for controlling keyhole stability and optimizing the process parameters in keyhole plasma arc welding.

Research on Correlation between Weld Concavity and Weld Process Parameters in Tailored Blank Laser Welding

Weld quality control is of great importance in tailored blank laser welding for the purpose of making products at a high quality and high productivity. In general, the controllable parameters are only indirect data on features of the final weld to be made. In this paper, direct correlation between weld concavity and weld process parameters including weld gap and torch offset are discussed based on theoretical analyses and experiments. A direct control model is established according to the analysis of reasons causing weld concavity. This model will improve the quality of laser welding process by accurately controlling the weld geometry in real time.

Visualization of coronary arteries using intravenous contrast agent and real-time 3-dimensional echocardiography in a patient with hypertrophic cardiomyopathy

Real-time 3-dimensional echocardiography is a recently developed imaging technique that provides unique information on spatial geometry in real time. We described an asymptomatic patient with hypertrophic obstructive cardiomyopathy for whom 3-dimensional echocardiography was performed after intravenous injection of perfluorocarbon-filled microbubbles. It resulted in enhancement of the left ventricular endocardial border delineation and myocardial perfusion in the hypertrophic septum. A clear visualization of the entire course of the left anterior descending coronary artery and its septal perforator branches was obtained. This case illustrates the potential of real-time 3-dimensional echocardiography to improve the anatomic evaluation of coronary arteries, especially when combined with contrast agents.

Neuro-Fuzzy 기법을 이용한 GMA 용접의 비드 형상에 대한 기하학적 추론 알고리듬 개발

One of the significant subject in the automatic arc welding is to establish control system of the welding parameters for controlling bead geometry as a criterion to evaluate the quality of arc welding. This paper proposes an inference algorithm for bead geometry in GMA Welding using Neuro-Fuzzy algorithm. The characteristic welding parameters are measured by the circuit composed of hall sensor, voltage divider tachometer. etc. and then the bead geometry of cach weld pool is calculated and detected by an image processing with CCD camera and a measuring with microscope. The relationships between the characteristic welding parameters and the bead geometry have been arranged empirically. From the result of experiments. membership functions and fuzzy rules are tuned and determined by the learning of neural network. and then the relationship between actual bead geometry and inferred bead geometry are concluded by fuzzy logic controller. In the applied inference system of bead geometry using Neuro-Fuzzy algorithm. the inference error percent is within -5% ~ +4% in case of bead width. -10%~+10% in bead height. -5%~+6% in bead area. -10%~+10% in penetration. Use of the Neuro-Fuzzy algorithm allows the GMA Welding system to evaluate the quality in bead geometry in real time as the welding parameters change.

A Study on Development of a New Algorithm for Predicting the Process Variables in GMA Welding Processes.

Gas Metal Arc (GMA) welding is extensively employed in the metal industries to weld a variety of ferrous and non-ferrous metals because of its potential for increasing the productivity and quality of welding which is controlled by the process parameters. The objective of this paper is to develop the algorithm that enables the determination of process variables from the optimized bead geometry for robotic GMA welding. It depends on the inversion of empirical equations derived from multiple regression analysis of the relationships between the process variables and the bead dimensions using the least square method. The method directly determines those variables which will give the desired set of bead geometry. This avoids the need to iterate with a succession of guesses employed Finite Element Method(FEM). These results suggest that process variable from experimental equation for robotic GMA welding may be employed to monitor and control the bead geometry in real time.

Process Control of Laser Grooving Using Acoustic Sensing

This paper discusses a closed-loop control concept for laser machining. A key development in the proposed control scheme is an acoustic sensor for inferring hole, kerf, and groove geometry in real time during laser machining. By sensing the acoustic signal emitted from the impingement of a gas jet on the erosion front, correlations between resonant frequency and hole, kerf or groove geometry were found. A process model was developed from applying the wave equation to the case of an elliptically-expanding or a constant-area jet. Experiments showed an inverse relationship between depth of cut and resonant frequency for grooving, cutting, and drilling cases. The paper also includes preliminary simulation results of a closed-lop control scheme for laser grooving using acoustic sensing and a PID controller.