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International Congress on Digital Heritage

作者： Matthias Zeppelzauer Georg Poiert Markus Seidl Christian Reinbacher Christian Breiteneder Horst Bischof Samuel Schulter Media Computing Group St. Pölten University of Applied Sciences Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Interactive Media Systems Group Vienna University of Technology Austria

Petroglyphs (rock engravings) are important artifacts for the documentation and analysis of early human life. Recent improvements in 3D scanning and 3D reconstruction enable the accurate 3D reconstruction of petroglyphs from rock surfaces at sub-millimeter resolution. To enable the indexing, matching, and recognition of petroglyphs in petroglyph databases, the shapes must first be segmented from the reconstructed rock surface. The absence of robust 3D segmentation methods for petroglyphs leaves a gap in the digital processing workflow. In this paper, we present a semi-automatic method for petroglyph segmentation for high-resolution 3D surface reconstructions. A comprehensive evaluation shows that our method is able to robustly segment petroglyphs with high accuracy and that the incorporation of 3D information is crucial to solve the segmentation problem. The presented method represents a major step towards the completion of a full 3D digital processing workflow of petroglyphs.

关键词： 3D segmentation semi-automatic segmentation surface texture analysis 3D rock-art analysis

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Cloud-based evaluation framework for big data

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2013 Annual Future Internet Assembly, FIA 2013

作者： Hanbury, Allan Müller, Henning Langs, Georg Menze, Bjoern H. Institute of Software Technology and Interactive Systems Vienna University of Technology Austria Switzerland CIR Lab. Department of Radiology Medical University of Vienna Austria Computer Vision Laboratory ETH Zürich Switzerland

ISBN: (纸本)9783642380815

The VISCERAL project is building a cloud-based evaluation framework for evaluating machine learning and information retrieval algorithms on large amounts of data. Instead of downloading data and running evaluations locally, the data will be centrally available on the cloud and algorithms to be evaluated will be programmed in computing instances on the cloud, effectively bringing the algorithms to the data. This approach allows evaluations to be performed on Terabytes of data without needing to consider the logistics of moving the data or storing the data on local infrastructure. After discussing the challenges of benchmarking on big data, the design of the VISCERAL system is presented, concentrating on the components for coordinating the participants in the benchmark and managing the ground truth creation. The first two benchmarks run on the VISCERAL framework will be on segmentation and retrieval of 3D medical images. © The Author(s).

关键词： Information retrieval

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VISCERAL: Towards large data in medical imaging - Challenges and directions

VISCERAL: Towards large data in medical imaging - Challenges...

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3rd MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CDS 2012

作者： Langs, Georg Hanbury, Allan Menze, Bjoern Müller, Henning Computational Image Analysis and Radiology Lab. Department of Radiology Medical University of Vienna Austria Institute for Software Technology and Interactive Systems Faculty of Computer Science Vienna University of Technology Austria Computer Vision Lab. ETH Zurich Switzerland Switzerland

ISBN: (纸本)9783642366772

The increasing amount of medical imaging data acquired in clinical practice holds a tremendous body of diagnostically relevant information. Only a small portion of these data are accessible during clinical routine or research due to the complexity, richness, high dimensionality and size of the data. There is consensus in the community that leaps in this regard are hampered by the lack of large bodies of data shared across research groups and an associated definition of joint challenges on which development can focus. In this paper we describe the objectives of the project Visceral. It will provide the means to jump-start this process by providing access to unprecedented amounts of real world imaging data annotated through experts and by using a community effort to generate a large corpus of automatically generated standard annotations. To this end, Visceral will conduct two competitions that tackle large scale medical image data analysis in the fields of anatomy detection, and content-based image retrieval, in this case the retrieval of similar medical cases using visual data and textual radiology reports. © 2013 Springer-Verlag.

关键词： Medical imaging

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Generalizing grasps across partly similar objects

Generalizing grasps across partly similar objects

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Renaud Detry Carl Henrik Ek Marianna Madry Justus Piater Danica Kragic Centre for Autonomous Systems and the Computer Vision and Active Perception Lab CSC KTH Royal Institute of Technology Stockholm Sweden Intelligent and Interactive Systems group Institute of Computer Science University of Innsbruck Austria

The paper starts by reviewing the challenges associated to grasp planning, and previous work on robot grasping. Our review emphasizes the importance of agents that generalize grasping strategies across objects, and that are able to transfer these strategies to novel objects. In the rest of the paper, we then devise a novel approach to the grasp transfer problem, where generalization is achieved by learning, from a set of grasp examples, a dictionary of object parts by which objects are often grasped. We detail the application of dimensionality reduction and unsupervised clustering algorithms to the end of identifying the size and shape of parts that often predict the application of a grasp. The learned dictionary allows our agent to grasp novel objects which share a part with previously seen objects, by matching the learned parts to the current view of the new object, and selecting the grasp associated to the best-fitting part. We present and discuss a proof-of-concept experiment in which a dictionary is learned from a set of synthetic grasp examples. While prior work in this area focused primarily on shape analysis (parts identified, e.g., through visual clustering, or salient structure analysis), the key aspect of this work is the emergence of parts from both object shape and grasp examples. As a result, parts intrinsically encode the intention of executing a grasp.

关键词： Grasping Shape Planning Dictionaries Databases Grippers Covariance matrix

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Granulometry based detection of junction and end points in patent drawings

Granulometry based detection of junction and end points in p...

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International Symposium on Image and Signal Processing and Analysis

作者： Naeem A. Bhatti Allan Hanbury Institute of Computer Aided Automation Computer Vision Laboratory Vienna University of Technology Vienna Austria Institute of Software Technology and Interactive Systems Vienna University of Technology Vienna Austria

In this paper, we propose an optimum detection of junction points and end points in patent drawings using morphological spurring and the granulometric curve of the image. The detection of these features in the skeletonized image gives rise to false detections due to skeletonization noise. An intersection of a spurred version of the skeleton image with the image containing junction points detection eradicates such false detections. To determine the optimum number of iterations for the spurring operation, the proposed approach takes into account the average thickness of lines found in the original image using the granulometric curve. The proposed method is parameter free, scale invariant and locates the positions of the junction points and end points accurately. We create ground truth of the junction points and end points and obtain the detection performance of the proposed method.

关键词： Biology

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Designing Immersive Virtual Reality for Geometry Education

Designing Immersive Virtual Reality for Geometry Education

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IEEE Annual International Symposium Virtual Reality

作者： H. Kaufmann D. Schmalstieg Institute of Software Technology and Interactive System University of Technology Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria

Our work introduces immersive collaborative learning to geometry education. More specifically, we present a system that uses collaborative augmented reality as a medium for teaching, and uses 3D dynamic geometry to facilitate mathematics and geometry education. Both these aspects are novel to geometry education. We describe improvements in the user interface and visual design of such an application. We also report on practical experiences with using our system for actual teaching of high school students, and present initial quantitative data on the educational value of such an approach.

关键词： Virtual reality computer science education User interfaces Computational geometry Collaborative work Augmented reality Educational technology computer interfaces Information geometry Mathematics

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Facial actions as visual cues for personality

Facial actions as visual cues for personality

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作者： Arya, Ali Jefferies, Lisa N. Enns, James T. DiPaola, Steve Imediatek Interactive Media Technologies Inc. 308 2131 West 3rd Avenue Vancouver BC V6K1L3 Canada IEEE IEEE Computer Society University of British Columbia Vision Sciences Society University of British Columbia Department of Psychology Graduate Program in Neuroscience Royal Society of Canada Simon Fraser University School of Interactive Arts and Technology Surrey BC Canada

What visual cues do human viewers use to assign personality characteristics to animated characters? While most facial animation systems associate facial actions to limited emotional states or speech content, the present paper explores the above question by relating the perception of personality to a wide variety of facial actions (e.g., head tilting/turning, and eyebrow raising) and emotional expressions (e.g., smiles and frowns). Animated characters exhibiting these actions and expressions were presented to human viewers in brief videos. Human viewers rated the personalities of these characters using a well-standardized adjective rating system borrowed from the psychological literature. These personality descriptors are organized in a multidimensional space that is based on the orthogonal dimensions of desire for affiliation and displays of social dominance. The main result of the personality rating data was that human viewers associated individual facial actions and emotional expressions with specific personality characteristics very reliably. In particular, dynamic facial actions such as head tilting and gaze aversion tended to spread ratings along the dominance dimension, whereas facial expressions of contempt and smiling tended to spread ratings along the affiliation dimension. Furthermore, increasing the frequency and intensity of the head actions increased the perceived social dominance of the characters. We interpret these results as pointing to a reliable link between animated facial actions/expressions and the personality attributions they evoke in human viewers. The paper shows how these findings are used in our facial animation system to create perceptually valid personality profiles based on dominance and affiliation as two parameters that control the facial actions of autonomous animated characters. Copyright © 2006 John Wiley & Sons, Ltd.

关键词： Face recognition

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Evaluating the effects of displaying uncertainty in context-aware applications

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3205卷 54-69页

作者： Antifakos, Stavros Schwaninger, Adrian Schiele, Bernt Perceptual Computing and Computer Vision ETH Zurich Tübingen Germany Department of Psychology University of Zurich Tübingen Switzerland Max Planck Institute for Biological Cybernetics Tübingen Germany Multimodal Interactive Systems Darmstadt University of Technology Germany

Many context, aware systems assume that the context information they use is highly accurate. In reality, however, perfect and reliable context information is hard if not impossible to obtain. Several researchers have therefore argued that proper feedback such as monitor and control mechanisms have to be employed in order to make context aware systems applicable and useable in scenarios of realistic complexity. As of today, those feedback mechanisms are difficult to compare since they are too rarely evaluated. In this paper we propose and evaluate a simple but effective feedback mechanism for context aware systems. The idea is to explicitly display the uncertainty inherent in the context information and to leverage from the human ability to deal well with uncertain information. In order to evaluate the effectiveness of this feedback mechanism the paper describes two user studies which mimic a ubiquitous memory aid. By changing the quality, respectively the uncertainty of context recognition, the experiments show that human performance in a memory task is increased by explicitly displaying uncertainty information. Finally, we discuss implications of these experiments for today's context-aware systems. © Springer-Verlag 2004.

关键词： Feedback control

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A model for human interruptability: experimental evaluation and automatic estimation from wearable sensors

A model for human interruptability: experimental evaluation ...

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International Symposium on Wearable computers

作者： N. Kern S. Antifakos B. Schiele A. Schwaninger Multimodal Interactive Systems Darmstadt University of Technology Germany Perceptual Computing and Computer Vision ETH Zurich Switzerland Department of Psychology University of Zurich Switzerland Max-Planck Institute of Biological Cybernetics Tubingen Germany

For the estimation of user interruptability in wearable and mobile settings, we propose in (N. Kern et al., 2003) to distinguish between the users' personal and social interruptability. In this paper, we verify this thesis with a user study on 24 subjects. Results show that there is a significant difference between social and personal interruptability. Further, we present a novel approach to estimate the social and personal interruptability of a user from wearable sensors. It is scalable for a large number of sensors, contexts, and situations and allows for online adaptation during run-time. We have developed a wearable platform, that allows to record and process the data from a microphone, 12 body-worn 3D acceleration sensors, and a location estimation. We have evaluated the approach on three different data sets, with a maximal length of two days.

关键词： Humans Wearable sensors Pervasive computing Wearable computers Biomedical monitoring Acceleration computer vision Microphones Costs Unsupervised learning

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