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SHREC'19 track: Extended 2D scene sketch-based 3D scene retrieval 12

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SHREC'19 track: Extended 2D scene sketch-based 3D scene retr...

12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer graphics, EG 2019

作者： Yuan, Juefei Abdul-Rashid, Hameed Li, Bo Lu, Yijuan Schreck, Tobias Bui, Ngoc-Minh Do, Trong-Le Nguyen, Khac-Tuan Nguyen, Thanh-An Nguyen, Vinh-Tiep Tran, Minh-Triet Wang, Tianyang School of Computing Sciences and Computer Engineering University of Southern Mississippi United States Department of Computer Science Texas State University United States Institute of Computer Graphics and Knowledge Visualization Graz University of Technology Austria Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Software Engineering Lab Vietnam National University Ho Chi Minh City Viet Nam University of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Department of Computer Science and Information Technology Austin Peay State University United States

ISBN: (纸本)9783038680772

Sketch-based 3D scene retrieval is to retrieve 3D scene models given a user's hand-drawn 2D scene sketch. It is a brand new but also very challenging research topic in the field of 3D object retrieval due to the semantic gap in their representations: 3D scene models or views differ from non-realistic 2D scene sketches. To boost this interesting research, we organized a 2D Scene Sketch-Based 3D Scene Retrieval track in SHREC'18, resulting a SceneSBR18 benchmark which contains 10 scene classes. In order to make it more comprehensive, we have extended the number of the scene categories from the initial 10 classes in the SceneSBR2018 benchmark to 30 classes, resulting in a new and more challenging benchmark SceneSBR2019 which has 750 2D scene sketches and 3,000 3D scene models. Therefore, the objective of this track is to further evaluate the performance and scalability of different 2D scene sketch-based 3D scene model retrieval algorithms using this extended and more comprehensive new benchmark. In this track, two groups from USA and Vietnam have successfully submitted 4 runs. Based on 7 commonly used retrieval metrics, we evaluate their retrieval performance. We have also conducted a comprehensive analysis and discussion of these methods and proposed several future research directions to deal with this challenging research topic. Deep learning techniques have been proved their great potentials again in dealing with this challenging retrieval task, in terms of both retrieval accuracy and scalability to a larger dataset. We hope this publicly available benchmark, together with its evaluation results and source code, will further enrich and promote 2D scene sketch-based 3D scene retrieval research area and its corresponding applications. © 2019 The Author(s)

关键词： Scalability

DETERMINATION of DETAILED MORPHOLOGICAL FEATURES for PHENOTYPING of SUGAR BEET PLANTS USING 3D-STEREOSCOPIC DATA 1

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DETERMINATION of DETAILED MORPHOLOGICAL FEATURES for PHENOTY...

1st Photogrammetric Image Analysis and Munich Remote Sensing Symposium, PIA 2019+MRSS 2019

作者： Scholz, O. Uhrmann, F. Wolff, A. Pieger, K. Penk, D. Fraunhofer Development Center X-ray Technology Fürth90768 Germany Strube Research GmbH Hauptstr. 1 Söllingen38387 Germany Friedrich-Alexander University Erlangen-Nuremberg Computer Graphics Group Erlangen91058 Germany

The sugar beet is the primary source of sugar in Europe and large parts of the world. Tools to determine plant traits with high precision and high throughput are required for the breeding process to quantify the effects of genetic and environmental factors on plant development and yield. In this work, we propose a method to gain a limited yet significant set of descriptive parameters for sugar beet plants. Using optical methods, a 3D representation of each plant is generated and subsequently segmented manually. A customized leaf model developed specifically for sugar beet plants then models the leaves, yielding a vector of descriptive parameters for each leaf. The resulting data is then compared to plant assessments of the same plants performed by sugar beet experts in order to evaluate the viability of automatic plant assessment in the sugar beet breeding process. © 2019 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. All rights reserved.

关键词： Remote sensing

Direct limit volumes: Constant-time limit evaluation for Catmull-clark solids 26

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Direct limit volumes: Constant-time limit evaluation for Cat...

26th Pacific Conference on computer graphics and Applications, Pacific graphics 2018

作者： Altenhofen, C. Müller, J. Weber, D. Stork, A. Fellner, D.W. Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Technische Universität Darmstadt Darmstadt Germany Graz University of Technology Institute of Computer Graphics and Knowledge Visualization Graz Austria

ISBN: (纸本)9783038680734

We present a novel approach for efficient limit volume evaluation on Catmull-Clark (CC) subdivision solids. Although several analogies exist between subdivision surfaces and subdivision volumes, extending Stam’s limit evaluation technique from 2 to 3 dimensions is not straightforward, as irregularities and boundaries introduce new challenges in the volumetric case. We present new direct evaluation techniques for irregular volumetric topologies and boundary cells, which allow for calculating the limit of CC subdivision solids at arbitrary parameter values in constant time. Evaluation of limit points is a central aspect when using CC solids for applications such as simulation and multi-material additive manufacturing, or as a compact volumetric representation scheme for continuous scalar fields. We demonstrate that our approach is faster than existing evaluation techniques for every topological configuration or target parameter (u, v, w) that requires more than two local subdivision steps. © 2018 The Author(s).

关键词： Topology

The creation of 2.5D animation for children self-discipline development 3

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The creation of 2.5D animation for children self-discipline ...

3rd International Conference on Digital Arts, Media and technology, ICDAMT 2018

作者： Suchat, Ratanapat Division of Computer Graphics and Multimedia School of Information and Communication Technology University of Phayao Phayao Thailand

ISBN: (纸本)9781509052097

This research aims to 1) create an animation in order to educate Thai children with self-discipline through the use of 2.5D animation technique which is a form of animation that relies on 3D objects within a 2D environment. 2) To study the kindergarten student's perception of such media and its satisfaction which there were the limits of research such as the population area included Phayao Kindergarten, paralleled with the population scope which was the 12 students of Kindergarten 2 and their 2 teachers within the concept of animation that interpreted 3 parts of self-discipline for instance, 1) Queuing 2) Punctuality and 3) Organizing thing in order. © 2018 IEEE.

关键词： Animation

ConceptExplorer: Visual Analysis of Concept Drifts in Multi-source Time-series Data

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ConceptExplorer: Visual Analysis of Concept Drifts in Multi-...

IEEE Symposium on Visual Analytics Science and technology (VAST)

作者： Xumeng Wang Wei Chen Jiazhi Xia Zexian Chen Dongshi Xu Xiangyang Wu Mingliang Xu Tobias Schreck State Key Lab of CAD&CG Zhejiang University School of Computer Science and Engineering Central South University College of Information Engineering China Jiliang University Institute of Graphics and Image Hangzhou Dianzi University Zhengzhou University Graz University of Technology

ISBN: (数字)9781728180090

ISBN: (纸本)9781728180106

Time-series data is widely studied in various scenarios, like weather forecast, stock market, customer behavior analysis. To comprehensively learn about the dynamic environments, it is necessary to comprehend features from multiple data sources. This paper proposes a novel visual analysis approach for detecting and analyzing concept drifts from multi-sourced time-series. We propose a visual detection scheme for discovering concept drifts from multiple sourced time-series based on prediction models. We design a drift level index to depict the dynamics, and a consistency judgment model to justify whether the concept drifts from various sources are consistent. Our integrated visual interface, ConceptExplorer, facilitates visual exploration, extraction, understanding, and comparison of concepts and concept drifts from multi-source time-series data. We conduct three case studies and expert interviews to verify the effectiveness of our approach.

关键词： Predictive models Data visualization Data models Adaptation models Indexes Analytical models Visual analytics

Lithography-free Plasmonic color printing with Femtosecond laser on Semicontinuous silver films

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arXiv 2020年

作者： Chowdhury, Sarah Nahar Nyga, Piotr Kudyshev, Zhaxylyk A. Bravo, Esteban Garcia Lagutchev, Alexei S. Kildishev, Alexander V. Shalaev, Vladimir M. Boltasseva, Alexandra School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University 1205 W State St West LafayetteIN47907 United States Institute of Optoelectronics Military University of Technology 2 Kaliskiego St Warsaw00-908 Poland Department of Computer Graphics Technology Purdue University Knoy Hall 401 N. Grant St West LafayetteIN47907 United States

Plasmonic color printing with semicontinuous metal films is a lithography-free and environment-friendly method for generating non-fading bright colors. Such films are comprised of islands – metal nanoparticles and their clusters of various dimensions, which resonate at different wavelengths upon external light illumination depending on the size and shape of the local particle structures. To experimentally realize systems that were optimized for achieving a broad color range and increased stability, various silver semicontinuous metal films were deposited on a metallic (Ag) mirror with a sub-wavelength-thick dielectric (SiO2) spacer. Femtosecond laser post-processing was then introduced to extend the color gamut through spectrally induced changes from blue to green, red, and yellow. Long-term stability and durability of the structures were addressed to enable non-fading colors with an optimized overcoating dielectric layer. The thickness of the proposed design is on the order of 100 nanometers, and it can be deposited on any substrate. These structures generate a broad range of long-lasting colors in reflection that can be applied to real-life artistic or technological applications with a spatial resolution on the order of 0.3 mm or less. Copyright © 2020, The Authors. All rights reserved.

关键词： Color

Patch augmentation: Towards efficient decision boundaries for neural networks

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arXiv 2019年

作者： Bloice, Marcus D. Roth, Peter M. Holzinger, Andreas Institute for Medical Informatics Statistics and Documentation Medical University Graz Institute of Computer Graphics and Vision Graz University of Technology

In this paper we propose a new augmentation technique, called patch augmentation, that, in our experiments, improves model accuracy and makes networks more robust to adversarial attacks. In brief, this data-independent approach creates new image data based on image/label pairs, where a patch from one of the two images in the pair is superimposed on to the other image, creating a new augmented sample. The new image's label is a linear combination of the image pair's corresponding labels. Initial experiments show a several percentage point increase in accuracy on CIFAR-10, from a baseline of approximately 81% to 89%. CIFAR-100 sees larger improvements still, from a baseline of 52% to 68% accuracy. Networks trained using patch augmentation are also more robust to adversarial attacks, which we demonstrate using the Fast Gradient Sign Method. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

Efficient MedSAMs: Segment Anything in Medical Images on Laptop

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

MFR 2021: Masked Face Recognition Competition

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arXiv 2021年

作者： Boutros, Fadi Damer, Naser Kolf, Jan Niklas Raja, Kiran Kirchbuchner, Florian Ramachandra, Raghavendra Kuijper, Arjan Fang, Pengcheng Zhang, Chao Wang, Fei Montero, David Aginako, Naiara Sierra, Basilio Nieto, Marcos Erakın, Mustafa Ekrem Demir, Ugur Ekenel, Hazım Kemal Kataoka, Asaki Ichikawa, Kohei Kubo, Shizuma Zhang, Jie He, Mingjie Han, Dan Shan, Shiguang Grm, Klemen Štruc, Vitomir Seneviratne, Sachith Kasthuriarachchi, Nuran Rasnayaka, Sanka Neto, Pedro C. Sequeira, Ana F. Pinto, Joao Ribeiro Saffari, Mohsen Cardoso, Jaime S. Fraunhofer Institute for Computer Graphics Research IGD Germany TU Darmstadt Germany Norwegian University of Science and Technology Norway TYAI China VICOMTECH Spain University of the Basque Country Spain SiMiT Lab Istanbul Technical University Turkey ACES Inc Japan Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China University of Ljubljana Slovenia University of Melbourne Australia University of Moratuwa Sri Lanka National University of Singapore Singapore INESC TEC Portugal University of Porto Portugal

This paper presents a summary of the Masked Face Recognition Competitions (MFR) held within the 2021 International Joint Conference on Biometrics (IJCB 2021). The competition attracted a total of 10 participating teams with valid submissions. The affiliations of these teams are diverse and associated with academia and industry in nine different countries. These teams successfully submitted 18 valid solutions. The competition is designed to motivate solutions aiming at enhancing the face recognition accuracy of masked faces. Moreover, the competition considered the deployability of the proposed solutions by taking the compactness of the face recognition models into account. A private dataset representing a collaborative, multisession, real masked, capture scenario is used to evaluate the submitted solutions. In comparison to one of the top-performing academic face recognition solutions, 10 out of the 18 submitted solutions did score higher masked face verification accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Biometrics