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arXiv 2020年

作者： Li, Jianning Pepe, Antonio Gsaxner, Christina Egger, Jan Institute of Computer Graphics and Vision Graz University of Technology Computer Algorithms for Medicine Laboratory Graz Austria Department of Oral and Maxillofacial Surgery Medical University of Graz

We introduce a fully automatic system for cranial implant design, a common task in cranioplasty operations. The system is currently integrated in Studierfenster (http://***/), an online, cloud-based medical image processing platform for medical imaging applications. Enhanced by deep learning algorithms, the system automatically restores the missing part of a skull (i.e., skull shape completion) and generates the desired implant by subtracting the defective skull from the completed skull. The generated implant can be downloaded in the STereoLithography (.stl) format directly via the browser interface of the system. The implant model can then be sent to a 3D printer for in loco implant manufacturing. Furthermore, thanks to the standard format, the user can thereafter load the model into another application for post-processing whenever necessary. Such an automatic cranial implant design system can be integrated into the clinical practice to improve the current routine for surgeries related to skull defect repair (e.g., cranioplasty). Our system, although currently intended for educational and research use only, can be seen as an application of additive manufacturing for fast, patient-specific implant design. Copyright © 2020, The Authors. All rights reserved.

关键词： 3D printers

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SAILOR: Scaling Anchors via Insights into Latent Object Representation

arXiv

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arXiv 2022年

作者： Malić, Dušan Fruhwirth-Reisinger, Christian Possegger, Horst Bischof, Horst Institute of Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Embedded Machine Learning Austria

LiDAR 3D object detection models are inevitably biased towards their training dataset. The detector clearly exhibits this bias when employed on a target dataset, particularly towards object sizes. However, object sizes vary heavily between domains due to, for instance, different labeling policies or geographical locations. State-of-the-art unsupervised domain adaptation approaches outsource methods to overcome the object size bias. Mainstream size adaptation approaches exploit target domain statistics, contradicting the original unsupervised assumption. Our novel unsupervised anchor calibration method addresses this limitation. Given a model trained on the source data, we estimate the optimal target anchors in a completely unsupervised manner. The main idea stems from an intuitive observation: by varying the anchor sizes for the target domain, we inevitably introduce noise or even remove valuable object cues. The latent object representation, perturbed by the anchor size, is closest to the learned source features only under the optimal target anchors. We leverage this observation for anchor size optimization. Our experimental results show that, without any retraining, we achieve competitive results even compared to state-of-the-art weakly-supervised size adaptation approaches. In addition, our anchor calibration can be combined with such existing methods, making them completely unsupervised. © 2022, CC BY.

关键词： Anchors

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A two-stage Otsu'S thresholding based method on a 2D histogram

A two-stage Otsu'S thresholding based method on a 2D histogr...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Puthipong Sthitpattanapongsa Thitiwan Srinark Graphics Innovation and Vision Engineering (GIVE) Laboratory Department of Computer Engineering Faculty of Engineering Kasetsart University Bangkok Thailand

We propose a fast and robust thresholding method that can overcome the shortcoming of the traditional and two-dimensional (2D) Otsu's methods. Our method takes advantage of the gradient gray level to divide the 2D histogram region, and applies the traditional Otsu's thresholding method twice on two projection histograms to separate the regions of interest from the background. The experimental results show that our method is robust against noise, and it requires less computational time than the 2D Otsu's and four other thresholding methods, which also give highly satisfactory and comparable results.

关键词： Histograms Magnetohydrodynamics Image segmentation Gaussian noise Robustness Shape

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Tablet versus phone: Depth perception in handheld augmented reality

Tablet versus phone: Depth perception in handheld augmented ...

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International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Arindam Dey Graeme Jarvis Christian Sandor Gerhard Reitmayr University of South Australia Adelaide SA AU Magic Vision Laboratory University of South Australia Institute of Computer Graphics and Vision Graz University of Technology

Augmented Reality (AR) applications on mobile devices like smartphones and tablet computers have become increasingly popular. In this paper, for the first time in the AR domain, we present: (1) the influence of different handheld displays and (2) the exocentric depth perception. Unlike egocentric depth perception, exocentric depth perception has not been investigated in AR. We have selected a suitable vision-based tracking method for our user studies based on a set of evaluations. Then we have investigated the effect of display size and resolution through two user studies. One study investigated the effect of different displays on egocentric depth perception. The other study investigated the effect of displays on exocentric and ordinal depth perception. Interestingly, we noticed depth compression is less when using a mobile phone, while participants subjectively preferred a tablet. A similar effect was also noticed in exocentric depth perception. The tablet provided significantly better ordinal depth perception and faster response time than the mobile phone. In both of the studies, we found no effect of the AR X-ray visualization on depth perception. Both egocentric and exocentric distances were underestimated.

关键词： Visualization Mobile handsets Cameras Target tracking Mobile communication Estimation

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Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Gayane Shalunts Yll Haxhimusa Robert Sablatnig Institute of Computer Aided Automation Computer Vision Laboratory University of Technology Vienna Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab University of Technology Vienna Austria

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate.

关键词： Shape Three dimensional displays Visualization computer vision Histograms Windows

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A Multi-Armed Bandits Learning-Based Approach to Service Caching in Edge Computing Environment 30th

A Multi-Armed Bandits Learning-Based Approach to Service Ca...

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30th International Conference on Web Services, ICWS 2023

作者： Li, Jinpeng Zhao, Jiale Chen, Peng Xia, Yunni Li, Fan Li, Yin Zeng, Feng Liu, Hui School of Computer Chongqing University Chongqing400030 China School of Computer and Software Engineering Xihua University Chengdu610039 China Key Laboratory of Fundamental Synthetic Vision Graphics and Image Science for National Defense Sichuan University Chengdu610065 China Guangzhou Institute of Software Application Technology Guangzhou510990 China Limited Shenzhen518129 China School of Computer Science and Technology Beijing Institute of Technology Beijing100083 China

ISBN: (纸本)9783031448355

Mobile edge computing (MEC) is a newly emerging concept that provides significant local computing power and reduces end-to-end latency. In MEC environments, caching frequently accessed services on edge servers effectively reduces latency and improves system responsiveness. An ongoing research topic in such a cachable MEC context is to design novel algorithms for yielding high-quality caching decision that guarantee high user-perceived quality-of-service (QoS) and high system responsiveness of delivery of cached content with the difference of caching capacities of edge servers and diversified content popularity appropriately addressed. In this article, we propose a multi-armed bandits learning-based method busing a Thompson sampling for generating caching decisions. We introduce a genetic multi-armed bandits algorithm (GMAB), which synthesizes the genetic algorithm (GA) and multi-armed bandits (MAB), for optimizing caching effectiveness with timing and space constraints. The experiment results show that GMAB outperforms traditional methods in terms of multiple aspects. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Genetic algorithms

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Using Image Morphing for Memory-Efficient Impostor Rendering on GPU

Using Image Morphing for Memory-Efficient Impostor Rendering...

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International Conference on Cyberworlds

作者： Kamer Ali Yuksel Aytul Ercil Alp Yucebilgin Selim Balcisoy Computer Vision and Pattern Analysis Laboratory Faculty of Engineering and Natural Sciences Sabanci University Istanbul Turkey Faculty of Engineering and Natural Sciences Computer Graphics Laboratory Sabanci University Istanbul Turkey

Real-time rendering of large animated crowds consisting thousands of virtual humans is important for several applications including simulations, games and interactive walkthroughs, but cannot be performed using complex polygonal models at interactive frame rates. For that reason, several methods using large numbers of pre-computed image-based representations, which are called as impostors, have been proposed. These methods take the advantage of existing programmable graphics hardware to compensate the computational expense while maintaining the visual fidelity. Making the number of different virtual humans, which can be rendered in real-time, not restricted anymore by the required computational power but by the texture memory consumed for the variety and discretization of their animations. In this work, we proposed an alternative method that reduces the memory consumption by generating compelling intermediate textures using image-morphing techniques. In order to demonstrate the preserved perceptual quality of animations, where half of the key-frames were rendered using the proposed methodology, we have implemented the system using the graphical processing unit and obtained promising results at interactive frame rates.

关键词： Rendering (computer graphics) Animation graphics processing unit Memory management Cameras Face Humans

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An interactive augmented reality coloring book

An interactive augmented reality coloring book

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International Symposium on Mixed and Augmented Reality (ISMAR)

作者： Adrian Clark Andreas Dünser Raphaël Grasset The HIT Laboratory NZ University of Canterbury Christchurch New Zealand Institute for Computer Graphics and Vision Graz University of Technology Austria

Creating entertaining and educational books not only requires providing visually stimulating content but also means for students to interact, create, and express themselves. In this paper we present a new type of mixed-reality book experience, which augments an educational coloring book with user-generated three dimensional content. We explore a “pop-up book” metaphor and describe a process by which children's drawing and coloring is used as input to generate and change the appearance of the book content. Our system is based on natural feature tracking and image processing techniques that can be easily exploited for other AR publishing applications.

关键词： Image color analysis Books Augmented reality Solid modeling Three dimensional displays Education Real time systems

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Neural human video rendering by learning dynamic textures and rendering-to-video translation

arXiv

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arXiv 2020年

作者： Liu, Lingjie Xu, Weipeng Habermann, Marc Zollhöfer, Michael Bernard, Florian Kim, Hyeongwoo Wang, Wenping Theobalt, Christian The Department of Computer Science The University of Hong Kong Hong Kong The Graphics Vision and Video Group Max Planck Institute for Informatics Saarbrücken66123 Germany The Department of Computer Science Computer Graphics Laboratory Stanford University CA94305 United States

Synthesizing realistic videos of humans using neural networks has been a popular alternative to the conventional graphics-based rendering pipeline due to its high efficiency. Existing works typically formulate this as an image-to-image translation problem in 2D screen space, which leads to artifacts such as over-smoothing, missing body parts, and temporal instability of fine-scale detail, such as pose-dependent wrinkles in the clothing. In this paper, we propose a novel human video synthesis method that approaches these limiting factors by explicitly disentangling the learning of time-coherent fine-scale details from the embedding of the human in 2D screen space. More specifically, our method relies on the combination of two convolutional neural networks (CNNs). Given the pose information, the first CNN predicts a dynamic texture map that contains time-coherent high-frequency details, and the second CNN conditions the generation of the final video on the temporally coherent output of the first CNN. We demonstrate several applications of our approach, such as human reenactment and novel view synthesis from monocular video, where we show significant improvement over the state of the art both qualitatively and quantitatively. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolutional neural networks

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TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering

arXiv

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arXiv 2023年

作者： Lin, Wei Kukleva, Anna Possegger, Horst Kuehne, Hilde Bischof, Horst Institute of Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Semantic 3D Computer Vision Austria Max-Planck-Institute for Informatics Germany Goethe University Frankfurt Germany

Temporal action segmentation in untrimmed videos has gained increased attention recently. However, annotating action classes and frame-wise boundaries is extremely time consuming and cost intensive, especially on large-scale datasets. To address this issue, we propose an unsupervised approach for learning action classes from untrimmed video sequences. In particular, we propose a temporal embedding network that combines relative time prediction, feature reconstruction, and sequence-to-sequence learning, to preserve the spatial layout and sequential nature of the video features. A two-step clustering pipeline on these embedded feature representations then allows us to enforce temporal consistency within, as well as across videos. Based on the identified clusters, we decode the video into coherent temporal segments that correspond to semantically meaningful action classes. Our evaluation on three challenging datasets shows the impact of each component and, furthermore, demonstrates our state-of-the-art unsupervised action segmentation results. Copyright © 2023, The Authors. All rights reserved.

关键词： Large dataset

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