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Medicine Meets Virtual Reality 16 - Parallel, Combinatorial, Convergent: NextMed by Design, MMVR 2008

作者： Quang Huy Viet, Huynh Hirai, Shinichi Shirai, Yoshiaki Yamaguchi, Satoshi Tanaka, Hiromi T. Kawasaki, Hiroshi Kawai, Yukiko Computer Vision and Graphics Laboratory Department of Information and Computer Science Saitama University Saitama Japan Laboratory for Integrated Machine Intelligence Department of Robotics Ritsumeikan University Kusatsu Japan Computer Vision Lab. Department of Human and Computer Intelligence Ritsumeikan University Kusatsu Japan Kawai Lab. Department of Computer Science Kyoto Sangyo University Kyoto Japan

ISBN: (纸本)9781586038229

On account of having real-time behavior and being easy to implement, spring meshes have been used for modeling deformable objects. Determining spring stiffness parameters for simulation of soft objects with high accuracy still remains a challenge. Allen Van Gelder derived an approximate formula for determining spring stiffness parameters based on strain analysis. Even though the experimental result showed the effectiveness, the method has not been investigated from a quantitative point of view. In this paper we propose a quantitative method for determining spring stiffness parameters. Moreover we propose a method to improve the accuracy by way of introducing torsional spring into the conventional spring mesh model. © 2008 The authors. All rights reserved.

关键词： Stiffness matrix

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IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions 32

IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo ba...

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32nd British Machine vision Conference, BMVC 2021

作者： Sormann, Christian Rossi, Mattia Kuhn, Andreas Fraundorfer, Friedrich Institute of Computer Graphics and Vision Graz University of Technology Austria Sony Europe B.V. R&D Center Stuttgart Laboratory 1 Germany

We present a novel deep-learning-based method for Multi-View Stereo. Our method estimates high resolution and highly precise depth maps iteratively, by traversing the continuous space of feasible depth values at each pixel in a binary decision fashion. The decision process leverages a deep-network architecture: this computes a pixelwise binary mask that establishes whether each pixel actual depth is in front or behind its current iteration individual depth hypothesis. Moreover, in order to handle occluded regions, at each iteration the results from different source images are fused using pixelwise weights estimated by a second network. Thanks to the adopted binary decision strategy, which permits an efficient exploration of the depth space, our method can handle high resolution images without trading resolution and precision. This sets it apart from most alternative learning-based Multi-View Stereo methods, where the explicit discretization of the depth space requires the processing of large cost volumes. We compare our method with state-of-the-art Multi-View Stereo methods on the DTU, Tanks and Temples and the challenging ETH3D benchmarks and show competitive results. © 2021. The copyright of this document resides with its authors.

关键词： Pixels

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A Three-Dimensional Edge Operator

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IEEE Transactions on Pattern Analysis and Machine Intelligence 1981年第3期PAMI-3卷 324-331页

作者： Zucker, Steven W. Hummel, Robert A. Computer Vision and Graphics Laboratory Department of Electrical Engineering McGill University Montreal P.Q. Canada Courant Institute New York University New York NY 10003 United States

Modern scanning techniques, such as computed tomography, have begun to produce true three-dimensional imagery of internal structures. The first stage in finding structure in these images, like that for standard two-dimensional images, is to evaluate a local edge operator over the image. If an edge segment in two dimensions is modeled as an oriented unit line segment that separates unit squares (Le., pixels) of different intensities, then a three-dimensional edge segment is an oriented unit plane that separates unit volumes (i.e., voxels) of different intensities. In this correspondence we derive an operator that finds the best oriented plane at each point in the image. This operator, which is based directly on the 3-D problem, complements other approaches that are either interactive or heuristic extensions of 2-D techniques. Copyright © 1981 by The Institute of Electrical and Electronics Engineers, Inc.

关键词： computerized tomography (CT) edge detection feature detection three-dimensional edge operators three-dimensional modeling

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Inferring Forces and Learning Human Utilities From Videos

Inferring Forces and Learning Human Utilities From Videos

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IEEE Conference on computer vision and Pattern Recognition

作者： Yixin Zhu Chenfanfu Jiang Yibiao Zhao Demetri Terzopoulos Song-Chun Zhu UCLA Center for Vision Cognition Learning and Autonomy UCLA Computer Graphics & Vision Laboratory

ISBN: (纸本)9781467388528

We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world objects, and introduce a learning framework that incorporates the concept of human utilities, which in our opinion provides a deeper and finer-grained account not only of object affordance but also of people's interaction with objects. Rather than defining affordance in terms of the geometric compatibility between body poses and 3D objects, we devise algorithms that employ physics-based simulation to infer the relevant forces/pressures acting on body parts. By observing the choices people make in videos (particularly in selecting a chair in which to sit) our system learns the comfort intervals of the forces exerted on body parts (while sitting). We account for people's preferences in terms of human utilities, which transcend comfort intervals to account also for meaningful tasks within scenes and spatiotemporal constraints in motion planning, such as for the purposes of robot task planning.

关键词： Three-dimensional displays Solid modeling Finite element analysis Planning Robots Biological system modeling Videos

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Hybrid Cutting of Deformable Solids

Hybrid Cutting of Deformable Solids

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IEEE Annual International Symposium Virtual Reality

作者： D. Steinemann M. Harders M. Gross G. Szekely Computer Graphics Laboratory ETH Zurich Switzerland Computer Vision Laboratory ETH Zurich Switzerland

A central training objective of virtual reality based surgical simulation is the removal of pathologic tissue. This necessitates stable, real-time updates of the underlying mesh representation. Within the framework of a hysteroscopy simulator, we have developed a hybrid cutting approach for tetrahedral meshes. It combines the topological update by subdivision with adjustments of the existing topology. Moreover, the mechanical and the visual model are decoupled, thus allowing different resolutions for the underlying mesh representations. With our method, we can closely approximate an arbitrary, user-defined cut surface while avoiding the creation of small or badly shaped elements, thus strongly reducing stability problems in the subsequent deformation computation. The presented approach has been integrated into a virtual reality training system for hysteroscopic interventions. The performance of the algorithm is demonstrated by examples of intra-uterine tumor ablations.

关键词： Solids Computational modeling Virtual reality Deformable models Laboratories Surgery Electrodes Cutting tools Pathology computer graphics

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Rotational alignment of imu-camera systems with 1-point ransac 2nd

Rotational alignment of imu-camera systems with 1-point rans...

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2nd Chinese Conference on Pattern Recognition and computer vision, PRCV 2019

作者： Guan, Banglei Su, Ang Li, Zhang Fraundorfer, Friedrich College of Aerospace Science and Engineering National University of Defense Technology Changsha China Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation Changsha China Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

ISBN: (纸本)9783030317256

In this paper we present a minimal solution for the rotational alignment of IMU-camera systems based on a homography formulation. The image correspondences between two views are related by homography when the motion of the camera can be effectively approximated as a pure rotation. By exploiting the rotational angles of the features obtained by e.g. the SIFT detector, we compute the rotational alignment of IMU-camera systems with only 1 feature correspondence. The novel minimal case solution allows us to cope with feature mismatches efficiently and robustly within a random sample consensus RANSAC scheme. Our method is evaluated on both synthetic and real scene data, demonstrating that our method is suited for the rotational alignment of IMU-camera systems. © Springer Nature Switzerland AG 2019.

关键词： Cameras

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Image Mosaic Based on SIFT and Deformation Propagation

Image Mosaic Based on SIFT and Deformation Propagation

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Li Yao Computer Graphics and Computer Vision Laboratory South-East University Nanjing China

This paper concerns the problem of automatic image stitching which mainly applies to the image sequence. Our proposed method gets the features based on scale invariant feature transform and finds the match pairs. Then we use feature deformation vectors and propagate them from the optimal partitions toward other pixels in the input images. The experiment results confirm the feasibility of our methods.

关键词： Cameras Feature extraction Image databases Spatial databases computer vision computer graphics Image sequences Pixel Brightness Radiometry

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CUDA and Applications to Task-based Programming

CUDA and Applications to Task-based Programming

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43rd Annual Conference on European Association for computer graphics, EUROgraphics 2022

作者： Kerbl, Bernhard Kenzel, Michael Winter, Martin Steinberger, Markus TU Wien Institute of Visual Computing and Human-Centered Technology Austria Saarland University Computer Graphics Lab Germany Intelligent Cloud Rendering Laboratory Huawei Technologies Austria Graz University of Technology Institute of Computer Graphics and Vision Austria

ISBN: (纸本)9783038681724

Since its inception, the CUDA programming model has been continuously evolving. Because the CUDA toolkit aims to consistently expose cutting-edge capabilities for general-purpose compute jobs to its users, the added features in each new version reflect the rapid changes that we observe in GPU architectures. Over the years, the changes in hardware, growing scope of built-in functions and libraries, as well as an advancing C++ standard compliance have expanded the design choices when coding for CUDA, and significantly altered the directives to achieve peak performance. In this tutorial, we give a thorough introduction to the CUDA toolkit, demonstrate how a contemporary application can benefit from recently introduced features and how they can be applied to task-based GPU scheduling in particular. For instance, we will provide detailed examples of use cases for independent thread scheduling, cooperative groups, and the CUDA standard library, libcu++, which are certain to become an integral part of clean coding for CUDA in the near future. © 2022 The Author(s)

关键词： Regulatory compliance

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Classifier grids for robust adaptive object detection

Classifier grids for robust adaptive object detection

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Peter M. Roth Sabine Sternig Helmut Grabner Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria Computer Vision Laboratory ETH Zurich Switzerland

In this paper we present an adaptive but robust object detector for static cameras by introducing classifier grids. Instead of using a sliding window for object detection we propose to train a separate classifier for each image location, obtaining a very specific object detector with a low false alarm rate. For each classifier corresponding to a grid element we estimate two generative representations in parallel, one describing the object's class and one describing the background. These are combined in order to obtain a discriminative model. To enable to adapt to changing environments these classifiers are learned on-line (i.e., boosting). Continuously learning (24 hours a day, 7 days a week) requires a stable system. In our method this is ensured by a fixed object representation while updating only the representation of the background. We demonstrate the stability in a long-term experiment by running the system for a whole week, which shows a stable performance over time. In addition, we compare the proposed approach to state-of-the-art methods in the field of person and car detection. In both cases we obtain competitive results.

关键词： Robustness Object detection Detectors Mesh generation Layout computer graphics computer vision Laboratories Cameras Boosting

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The improvement of the Helbing model based on the three-phase theory

The improvement of the Helbing model based on the three-phas...

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2nd International Conference on Transportation Engineering, ICTE 2009

作者： Sheng, Peng Liu, Yiguang Tang, Peng Gao, Lin Yang, Menglong School of Computer Science Sichuan University Chengdu 610064 China Key Laboratory of Fundamental Synthetic Vision Graphics and Image Science for National Defense Sichuan University Chengdu 610064 China

ISBN: (纸本)9780784410394

In this paper, we present an improved prefactor function of the Helbing model based on the three-phase theory. The new prefactor function takes into account multi critical points in the transition of traffic flow to calculate the fluctuation of synchronized flow. Corresponding to the new function, the primary expressions of the Helbing model have been improved to reflect the complex property of the overlap region in the transition. Then we process the empirical data and calibrate all parameters of the new model by the method similar to the Helbing's. As demonstrated by various examples and empirical data, the new model has simulated traffic flow closer to reality than before. Copyright ASCE 2009.

关键词： Helbing model Multi critical points Prefactor function Three-phase theory

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