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On-line boosting and vision

On-line boosting and vision

引用

2006 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2006

作者： Grabner, Helmut Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology

ISBN: (纸本)0769525970

Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which implies that all training data has to be a priori given;training and usage of the classifier are separate steps. Training the classifier on-line and incrementally as new data becomes available has several advantages and opens new areas of application for boosting in computer vision. In this paper we propose a novel on-line AdaBoost feature selection method. In conjunction with efficient feature extraction methods the method is real time capable. We demonstrate the multifariousness of the method on such diverse tasks as learning complex background models, visual tracking and object detection. All approaches benefit significantly by the on-line training. © 2006 IEEE.

关键词： Online systems

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Efficient Maximally Stable Extremal Region (MSER) tracking

Efficient Maximally Stable Extremal Region (MSER) tracking

引用

2006 IEEE computer Society Conference on computer vision and Pattern Recognition, CVPR 2006

作者： Donoser, Michael Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology

ISBN: (纸本)0769525970

This paper introduces a tracking method for the well known local MSER (Maximally Stable Extremal Region) detector. The component tree is used as an efficient data structure, which allows the calculation of MSERs in quasi-linear time. It is demonstrated that the tree is able to manage the required data for tracking. We show that by means of MSER tracking the computational time for the detection of single MSERs can be improved by a factor of 4 to 10. Using a weighted feature vector for data association improves the tracking stability. Furthermore, the component tree enables backward tracking which further improves the robustness. The novel MSER tracking algorithm is evaluated on a variety of scenes. In addition, we demonstrate three different applications, tracking of license plates, faces and fibers in paper, showing in all three scenarios improved speed and stability. © 2006 IEEE.

关键词： Pattern recognition

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Towards multiscale mesh denoising 04

Towards multiscale mesh denoising

引用

Spring Conference on computer graphics, SCCG 2004

作者： Grabner, Markus Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)1581139144

Recently developed methods address the problem of denoising polygonal meshes derived from automatic scanning procedures. Nonlinear filtering is applied iteratively based on the estimated statistical properties of errors associated with the measured vertex locations. This procedure requires a rather uniform sampling interval across the surface and cannot remove noise below a certain frequency due to the local support of the filter kernel. We consider an approach to remedy these problems by interleaving mesh denoising and mesh simplification based on the quadric error metric. Instead of directly operating on vertex locations, the error quadrics (which are evaluated to determine vertex locations) are manipulated. Therefore denoising is applied at different scales according to the progress of simplification, being less sensitive to varying resolution and low-frequency noise. This is work in progress, which reveals some interesting properties in the context of denoising and simplification. However, the desired results have not yet been achieved. Copyright © 2004 by the Association for Computing Machinery, Inc.

关键词： computer graphics

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Ray prioritization using stylization and visual saliency

Ray prioritization using stylization and visual saliency

引用

作者： Steinberger, Markus Kainz, Bernhard Hauswiesner, Stefan Khlebnikov, Rostislav Kalkofen, Denis Schmalstieg, Dieter Institute for Computer Graphics and Vision Graz University of Technology Austria

This paper presents a new method to control scene sampling in complex ray-based rendering environments. It proposes to constrain image sampling density with a combination of object features, which are known to be well perceived by the human visual system, and image space saliency, which captures effects that are not based on the objects geometry. The presented method uses Non-Photorealistic Rendering techniques for the object space feature evaluation and combines the image space saliency calculations with image warping to infer quality hints from previously generated frames. In order to map different feature types to sampling densities, we also present an evaluation of the object space and image space features impact on the resulting image quality. In addition, we present an efficient, adaptively aligned fractal pattern that is used to reconstruct the image from sparse sampling data. Furthermore, this paper presents an algorithm which uses our method in order to guarantee a desired minimal frame rate. Our scheduling algorithm maximizes the utilization of each given time slice by rendering features in the order of visual importance values until a time constraint is reached. We demonstrate how our method can be used to boost or stabilize the rendering time in complex ray-based image generation consisting of geometric as well as volumetric data. © 2012 Elsevier Ltd.

关键词： Volume rendering

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Compensation of motion artifacts for time-of-flight cameras

Compensation of motion artifacts for time-of-flight cameras

引用

DAGM Workshop on Dynamic 3D Imaging, Dyn3D 2009

作者： Lindner, Marvin Kolb, Andreas Institute for Vision and Graphics Computer Graphics and Multimedia Systems Group University of Siegen Germany

ISBN: (纸本)3642037771

During the last years, Time-of-Flight sensors achieved a significant impact onto research fields in computer vision. For dynamic scenes however, most sensor's working principles lead to significant artifacts in respect to sensor or object motion - artifacts that commonly affect distance reliability and thus affect downstream processing tasks in a negative way. We therefore introduce a compensation approach for sensors based on the Photonic Mixing Device (PMD). Out technique deals with both, lateral and axial motion artifacts. The lateral compensation tracks object motion on the level of phase images and accordingly adjusts the depth image computation in order to reduce artifacts and enhances depth reliability. The axial motion compensation is based on an axial motion estimation and a theoretical model for axial motion deviation errors. Both components utilize fast optical flow algorithms. © 2009 Springer Berlin Heidelberg.

关键词： Motion estimation

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Learning of scene-specific object detectors by classifier co-grids

Learning of scene-specific object detectors by classifier co...

引用

2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010

作者： Sternig, Sabine Roth, Peter M. Bischof, Horst Graz University of Technology Institute for Computer Graphics and Vision Austria

ISBN: (纸本)9780769542645

Recently, classifier grids have shown to be a considerable alternative to sliding window approaches for object detection from static cameras. The main drawback of such methods is that they are biased by the initial model. In fact, the classifiers can be adapted to changing environmental conditions but due to conservative updates no new object-specific information is acquired. Thus, the goal of this work is to increase the recall of scene-specific classifiers while preserving their accuracy and speed. In particular, we introduce a co-training strategy for classifier grids using a robust on-line learner. Thus, the robustness is preserved while the recall can be increased. The co-training strategy robustly provides negative as well as positive updates. In addition, the number of negative updates can be drastically reduced, which additionally speeds up the system. In the experimental results these benefits are demonstrated on different publicly available surveillance benchmark data sets. © 2010 IEEE.

关键词： Object detection

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Robust tracking of spatial related components

Robust tracking of spatial related components

引用

作者： Mauthner, Thomas Donoser, Michael Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9781424421756

This paper introduces a hierarchical approach for multi-component tracking, where the object-to-be-tracked is modeled as a group of spatial related parts. We propose to use a robust particle filtering framework for tracking the individual components and outline how the spatial coherency between the parts can be efficiently integrated by analyzing a two-level hierarchy of particle filters. Including spatial information allows to handle common tracking problems like occlusions, clutter or blur. Furthermore, the dynamic calculation of particle set uncertainties allows a dynamic adaption of stiffness values for the spatial model to e. g. force occluded parts to stay in spatial relation. The experimental section proves the robustness of the proposed tracker on challenging sequences of the VIVID-PETS database. © 2008 IEEE.

关键词： Monte Carlo methods

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Real time appearance based hand tracking

Real time appearance based hand tracking

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作者： Donoser, Michael Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9781424421756

This paper introduces a real-time method for tracking hands through image sequences. Our method combines efficiently calculated color likelihood maps with a modified version of the Maximally Stable Extremal Region (MSER)-tracker. The proposed algorithm allows to robustly track hands through image sequences and additionally provides accurate hand segmentations per frame. Experimental evaluation proves the high accuracy of the segmentation results and a first application for human-computer interaction is presented. © 2008 IEEE.

关键词： Human computer interaction

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Display-adaptive window management for irregular surfaces

Display-adaptive window management for irregular surfaces

引用

ACM International Conference on Interactive Tabletops and Surfaces, ITS 2011

作者： Waldner, Manuela Grasset, Raphael Steinberger, Markus Schmalstieg, Dieter Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9781450308717

Current projectors can easily be combined to create an everywhere display, using all suitable surfaces in offices or meeting rooms for the presentation of information. However, the resulting irregular display is not well supported by traditional desktop window managers, which are optimized for rectangular screens. In this paper, we present novel display-adaptive window management techniques, which provide semi-automatic placement for desktop elements (such as windows or icons) for users of large, irregularly shaped displays. We report results from an exploratory study, which reveals interesting emerging strategies of users in the manipulation of windows on large irregular displays and shows that the new techniques increase subjective satisfaction with the window management interface. © 2011 ACM.

关键词： Irregular displays Window management

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Multiple instance boosting for face recognition in videos

Multiple instance boosting for face recognition in videos

引用

Lecture Notes in computer Science

作者： Wohlhart, Paul Köstinger, Martin Roth, Peter M. Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9783642231223

For face recognition from video streams often cues such as transcripts, subtitles or on-screen text are available. This information could be very valuable for improving the recognition performance. However, frequently this data can not be associated directly with just one of the visible faces. To overcome this limitations and to exploit valuable information, we define the task as a multiple instance learning (MIL) problem. We formulate a robust loss function that describes our problem and incorporates ambiguous and unreliable information sources and optimize it using Gradient Boosting. A new definition of the posterior probability of a bag, based on the L p -norm, improves the ability to deal with varying bag sizes over existing formulations. The benefits of the approach are demonstrated for face recognition in videos on a publicly available benchmark dataset. In fact, we show that exploring new information sources can drastically improve the classification results. Additionally, we show its competitive performance on standard machine learning datasets. © 2011 Springer-Verlag.

关键词： Face recognition

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