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检索条件"机构=Perceptual Computing and Computer Vision Group"

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Proactive instructions for furniture assembly 4

引用

4th International Conference on Ubiquitous computing, UbiComp 2002

作者： Antifakos, Stavros Michahelles, Florian Schiele, Bernt Perceptual Computing and Computer Vision Group ETH Zurich Switzerland

ISBN: (纸本)3540442677

Tennenhouse [1] coined the term proactive computing where humans get out of the interaction loop and may be serviced specifically according to their needs and current situation. In this paper we propose a framework for proactive guidance which aims to overcome limitations of today’s printed instructions. By attaching computing devices and multi- ple sensors onto different parts of the assembly the system can recognize the actions of the user and determine the current state of the assembly. The system can suggest the next most appropriate action at any point in time. In an experimental case study with the IKEA PAX wardrobe we show the feasibility of the proposed approach. At the end important issues are discussed and future directions are outlined. © Springer-Verlag Berlin Heidelberg 2002.

关键词： computers

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Query-dependent performance optimization for vocabulary-supported image retrieval

Query-dependent performance optimization for vocabulary-supp...

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24th German Association for Pattern Recognition Symposium, DAGM 2002

作者： Vogel, Julia Schiele, Bernt Perceptual Computing and Computer Vision Group ETH Zurich Switzerland

ISBN: (纸本)354044209X

In[1], we proposed a two-stage retrieval framework which makes not only performance characterization but also performance optimization manageable. There, the performance optimization focused on the second stage of the retrieval framework. In this paper, we extend the method to a full two-stage performance characterization and optimization. In our retrieval framework, the user specifies a high-level concept to be searched for, the size of the image region to be covered by the concept (e.g."Search images with 30-50% of sky") and an optimization option (e.g. "maximum recall", "maximum precision" or "joint maximization of precision and recall"). For the detection of each concept such as "sky", a multitude of concept detectors exist that perform differently. In order to reach optimum retrieval performance, the detector best satisfying the user query is selected and the information of the corresponding concept detector is processed and optimized. Besides the optimization procedure itself the paper discusses the generation of multiple detectors per semantic concept. In experiments, the advantage of joint compared to individual optimization of first and second stage is shown. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Semantics

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An information-theoretic approach to combining object models

An information-theoretic approach to combining object models

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Intelligent Robotic Systems (SIRS 2002)

作者： Kruppa, Hannes Schiele, Bernt Perceptual Computing and Computer Vision Group ETH Zurich Zurich Switzerland

This paper introduces a new method for combining different object models. By determining a configuration of the models, which maximizes their mutual information, the proposed method creates a unified hypothesis from multiple object models on the fly without prior training. To validate the effectiveness of the proposed method, experiments are conducted in which human faces are detected and localized in images by combining different face models. © 2002 Elsevier Science B.V. All rights reserved.

关键词： computer aided analysis

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Multi-object tracking based on a modular knowledge hierarchy

Multi-object tracking based on a modular knowledge hierarchy

引用

Lecture Notes in computer Science

作者： Spengler, Martin Schiele, Bernt Perceptual Computing and Computer Vision Group Computer Science Department ETH Zurich Switzerland

An important goal of research in computer vision systems is to develop architectures which are general and robust and at the same time transparent and easily transferable from one domain to another. To this extent this paper discusses and demonstrates the versatility of a multi-object tracking framework based on the so called knowledge hierarchy. The systematic description and analysis of a priori knowledge provides means not only for reducing the complexity of the multi-object tracking problem but also for building modular systems for solving it. The modularity of the framework, an essential ingredient for versatility, allows to replace individual parts of an existing system without altering the rest of the system or the overall architecture. The paper presents the modular framework including the knowledge hierarchy for multi object tracking. In order to demonstrate the transferability of the proposed approach the tracking framework is then applied to three different tracking scenarios (parking lot surveillance, people interaction monitoring, and dining table setup). © Springer-Verlag Berlin Heidelberg 2003.

关键词： Tracking (position)

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Towards robust multi-cue integration for visual tracking 2

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2nd International Workshop on computer vision Systems, ICVS 2001

作者： Spengler, Martin Schiele, Bernt Perceptual Computing and Computer Vision Group Computer Science Department ETH Zurich Switzerland

ISBN: (纸本)3540422854

Even though many of today's vision algorithms are very successful, they lack robustness since they are typically limited to a particular situation. In this paper we argue that the principles of sensor and model integration can increase the robustness of today's computer vision systems substantially. As an example multi-cue tracking of faces is discussed. The approach is based on the principles of self-organization of the integration mechanism and self-adaptation of the cue models during tracking. Experiments show that the robustness of simple models is leveraged significantly by sensor and model integration. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Integration

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Skin patch detection in real-world images

Skin patch detection in real-world images

引用

24th Symposium of the German Pattern Recognition Association, DAGM 2002

作者： Kruppa, Hannes Bauer, Martin A. Schiele, Bernt Perceptual Computing and Computer Vision Group ETH Zurich Switzerland

ISBN: (纸本)354044209X

While human skin is relatively easy to detect in controlled environments, detection in uncontrolled settings such as in consumer digital photographs is generally hard. Algorithms need to robustly deal with variations in lighting, color resolution, and imaging noise. This paper proposes a simple generative skin patch model combining shape and color information. The model is parametric and represents the spatial arrangement of skin pixels as compact elliptical regions. Its parameters are estimated by maximizing the mutual information between the model-generated skin pixel distribution and the distribution of skin color as observed in the image. The core of this work is an empirical evaluation on a database of 653 consumer digital photographs. In addition, we investigate the potential of combining our skin detector with state-of-the-art appearance-based face detectors. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Pixels

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How many classifiers do I need?

How many classifiers do I need?

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作者： Schiele, Bernt Perceptual Computing and Computer Vision Group Computer Science Department ETH Zurich

Combining multiple classifiers promises to increase performance and robustness of a classification task. Currently however, the understanding which combination scheme should be used and the ability to quantify the expected benefit is inadequate. This paper attempts to quantify the performance and robustness gain for different combination schemes and for two classifier types. The results of the paper indicate that the combination of a small number of classifiers may already result in a substantial performance gain. Also, the increase in robustness can be substantial by combining an adequate number of classifiers. © 2002 IEEE.

关键词： Pattern recognition

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Beyond positionl awareness

Beyond positionl awareness

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作者： Antifakos, Stavros Schiele, Bernt Perceptual Computing and Computer Vision Group ETH Zurich CH08092 Zurich Switzerland

Location models are merely based on positional information. Using wireless sensor networks, however, allows us to extract information which can be related to different levels of semantic proximity of different devices. Based on this observation, the paper proposes a semantic proximity hierarchy based on a wireless sensor network. In this paper, we argue that the proposed proximity hierarchy adds a new and complementary dimension to pure positional location information. The paper discusses the proposed hierarchy, gives application examples and some preliminary experimental results. © Springer-Verlag London Ltd 2002.

关键词： Wireless sensor networks

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Integration of wireless gesture tracking, object tracking, and 3D reconstruction in the perceptive workbench 2

引用

2nd International Workshop on computer vision Systems, ICVS 2001

作者： Leibe, Bastian Minnen, David Weeks, Justin Starner, Thad Perceptual Computing and Computer Vision Group ETH Zurich Haldeneggsteig 4 ZurichCH-8092 Switzerland Contextual Computing Group GVU Center Georgia Institute of Technology Georgia

ISBN: (纸本)3540422854

The Perceptive Workbench endeavors to create a spontaneous and unimpeded interface between the physical and virtual worlds. Its vision-based methods for interaction constitute an alternative to wired input devices and tethered tracking. Objects are recognized and tracked when placed on the display surface. By using multiple infrared light sources, the object's 3D shape can be captured and inserted into the virtual interface. This ability permits spontaneity since either preloaded objects or those objects selected at run-time by the user can become physical icons. Integrated into the same vision-based interface is the ability to identify 3D hand position, pointing direction, and sweeping arm gestures. Such gestures can enhance selection, manipulation, and navigation tasks. In previous publications, the Perceptive Workbench has demonstrated its utility for a variety of applications, including augmented reality gaming and terrain navigation. This paper will focus on the implementation and performance aspects and will introduce recent enhancements to the system. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Virtual reality

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Analyzing appearance and contour based methods for object categorization

Analyzing appearance and contour based methods for object ca...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： B. Leibe B. Schiele Perceptual Computing and Computer Vision Group ETH Zurich Switzerland

Object recognition has reached a level where we can identify a large number of previously seen and known objects. However, the more challenging and important task of categorizing previously unseen objects remains largely unsolved. Traditionally, contour and shape based methods are regarded most adequate for handling the generalization requirements needed for this task. Appearance based methods, on the other hand, have been successful in object identification and detection scenarios. Today little work is done to systematically compare existing methods and characterize their relative capabilities for categorizing objects. In order to compare different methods we present a new database specifically tailored to the task of object categorization. It contains high-resolution color images of 80 objects from 8 different categories, for a total of 3280 images. It is used to analyze the performance of several appearance and contour based methods. The best categorization result is obtained by an appropriate combination of different methods.

关键词： Object recognition Shape computer vision Image databases Performance analysis Face detection Image segmentation Psychology Humans Object detection

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