This paper adopts the metaphor of representational fluency and proposes an auto linking approach to help analysts investigate details of suspicious sections across different cybersecurity visualizations. Analysis of s...
This paper adopts the metaphor of representational fluency and proposes an auto linking approach to help analysts investigate details of suspicious sections across different cybersecurity visualizations. Analysis of spatiotemporal network security data takes place both conditionally and in sequence. Many visual analytics systems use time series curves to visualize the data from the temporal perspective and maps to show the spatial information. To identify anomalies, the analysts frequently shift across different visualizations and the original data view. We consider them as various representations of the same data and aim to enhance the fluency of navigation across these representations. With the auto linking mechanism, after the analyst selects a segment of a curve, the system can automatically highlight the related area on the map for further investigation, and the selections on the map or the data views can also trigger the related time series curves. This approach adopts the slicing operation of the Online Analytical Process (OLAP) to find the basic granularities that contribute to the overall value change. We implemented this approach in an award-winning visual analytics system, SemanticPrism, and demonstrate the functions through two use cases.
This paper presents ongoing research aimed at improving building sustainability education through the use of serious games. With the growth of the population worldwide and the increased demand on resources, there has ...
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A large number of photographs of cultural heritage items and monuments is publicly available in various Open Access Image Repositories (OAIR) and social media sites. Metadata inserted by camera, user and host site may...
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We present a framework for the conversion of existing 3D unstructured urban models into a compact procedural representation that enables model synthesis, querying, and simplification of large urban areas. During the d...
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We present a framework for the conversion of existing 3D unstructured urban models into a compact procedural representation that enables model synthesis, querying, and simplification of large urban areas. During the de-instancing phase, a dissimilarity-based clustering is performed to obtain a set of building components and component types. During the proceduralization phase, the components are arranged into a context-free grammar, which can be directly edited or interactively manipulated. We applied our approach to convert several large city models, with up to 19,000 building components spanning over 180 km squares, into procedural models of a few thousand terminals, non-terminals, and 50-100 rules.
In recent years the operating speed of digital electronic systems has increased beyond one GHz. Challenges to the system design are electromagnetic compatibility and signal integrity issues. The electrical and compute...
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In recent years the operating speed of digital electronic systems has increased beyond one GHz. Challenges to the system design are electromagnetic compatibility and signal integrity issues. The electrical and computer engineering technology programs offer courses in digital and analog electronics, and communication circuits along with fundamentals of circuit analysis, signals and systems and electromagnetics. An elective course on Electromagnetic Compatibility (EMC) will provide students with knowledge of overcoming challenges of meeting standards and signal integrity issues and knowledge of dealing with electronic systems as a whole to the students. This paper discusses the contents of the curriculum to prepare students in technology major for this important industry relevant topic.
Mass Spring Model (MSM) is a highly efficient model in terms of calculations and easy implementation. Mass, spring stiffness coefficient and damping constant are three major components of MSM. This paper focuses on id...
Mass Spring Model (MSM) is a highly efficient model in terms of calculations and easy implementation. Mass, spring stiffness coefficient and damping constant are three major components of MSM. This paper focuses on identifying the coefficients of spring stiffness and damping constant using automated tuning method by optimization in generating human liver model capable of responding quickly. To achieve the objective two heuristic approaches are used, namely Simulated Annealing (SA) and Genetic Algorithm (GA) on the human liver model data set. The properties of the mechanical heart, which are taken into consideration, are anisotropy and viscoelasticity. Optimization results from SA and GA are then implemented into the MSM to model two human hearts, each with its SA or GA construction parameters. These techniques are implemented while making FEM construction parameters as benchmark. Step size response of both models are obtained after MSMs were solved using Fourth Order Runge-Kutta (RK4) to compare the elasticity response of both models. Remodelled time using manual calculation methods was compared against heuristic optimization methods of SA and GA in showing that model with automatic construction is more realistic in terms of realtime interaction response time. Liver models generated using SA and GA optimization techniques are compared with liver model from manual calculation. It shows that the reconstruction time required for 1000 repetitions of SA and GA is faster than the manual method. Meanwhile comparison between construction time of SA and GA model indicates that model SA is faster than GA with varying rates of time 0.110635 seconds/1000 repetitions. Real-time interaction of mechanical properties is dependent on rate of time and speed of remodelling process. Thus, the SA and GA have proven to be suitable in enhancing realism of simulated real-time interaction in liver remodelling.
Safety and health issues are important components for any industry that involves machinery operations. To control various hazards leading to occupational injuries and illnesses, one common method is safety training an...
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Safety and health issues are important components for any industry that involves machinery operations. To control various hazards leading to occupational injuries and illnesses, one common method is safety training and education. In this study, we developed a 3D virtual reality game to enhance safety training and education. Based on the recommendations from industrial partners, a pedestal grinder and its operation were selected for this study. The pedestal grinder and the mechanical laboratory were converted to three dimensional shapes using 3D modeling software. The completed 3D models were brought into the game engine to replicate actual laboratory environment. This allows students to interact within the virtual environment and be able to operate the virtual pedestal grinder safely. The interactivity between a user and the equipment within 3D virtual environment was implemented using visual programming tool inside the game engine. A pilot study was conducted to assess the students' learning with regard to the pedestal grinder safety using three groups: lecture only, lecture with physical laboratory, and lecture with the developed 3D virtual environment. The results indicated the benefits of 3D virtual reality game over “lecture only” delivery method in enhancing students' learning. Furthermore, virtual reality game allows students to retain information as good as the “lecture with physical laboratory” delivery method.
Our demo demonstrates the method we published at CVPR this year for tracking specular and poorly textured objects, and lets the visitors experiment with it and with their own patterns. Our approach only requires a sta...
Our demo demonstrates the method we published at CVPR this year for tracking specular and poorly textured objects, and lets the visitors experiment with it and with their own patterns. Our approach only requires a standard monocular camera (no need for a depth sensor), and can be easily integrated within existing systems to improve their robustness and accuracy.
We propose a robust and accurate method to extract the centerlines and scale of tubular structures in 2D images and 3D volumes. Existing techniques rely either on filters designed to respond to ideal cylindrical struc...
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ISBN:
(纸本)9781479951192
We propose a robust and accurate method to extract the centerlines and scale of tubular structures in 2D images and 3D volumes. Existing techniques rely either on filters designed to respond to ideal cylindrical structures, which lose accuracy when the linear structures become very irregular, or on classification, which is inaccurate because locations on centerlines and locations immediately next to them are extremely difficult to distinguish. We solve this problem by reformulating centerline detection in terms of a regression problem. We first train regressors to return the distances to the closest centerline in scale-space, and we apply them to the input images or volumes. The centerlines and the corresponding scale then correspond to the regressors local maxima, which can be easily identified. We show that our method outperforms state-of-the-art techniques for various 2D and 3D datasets.
In this paper we present a novel method to accurately estimate the dense 3D motion field, known as scene flow, from depth and intensity acquisitions. The method is formulated as a convex energy optimization, where the...
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In this paper we present a novel method to accurately estimate the dense 3D motion field, known as scene flow, from depth and intensity acquisitions. The method is formulated as a convex energy optimization, where the motion warping of each scene point is estimated through a projection and back-projection directly in 3D space. We utilize higher order regularization which is weighted and directed according to the input data by an anisotropic diffusion tensor. Our formulation enables the calculation of a dense flow field which does not penalize smooth and non-rigid movements while aligning motion boundaries with strong depth boundaries. An efficient parallelization of the numerical algorithm leads to runtimes in the order of 1s and therefore enables the method to be used in a variety of applications. We show that this novel scene flow calculation outperforms existing approaches in terms of speed and accuracy. Furthermore, we demonstrate applications such as camera pose estimation and depth image super resolution, which are enabled by the high accuracy of the proposed method. We show these applications using modern depth sensors such as Microsoft Kinect or the PMD Nano Time-of-Flight sensor.
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