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检索条件"机构=Computer Systems and Vision Lab"

共 262 条记录，以下是11-20 订阅

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Surface Reconstruction from Multiple Images Filtering Non-Lambert Regions

Surface Reconstruction from Multiple Images Filtering Non-La...

引用

16th IEEE International Conference on Image Processing

作者： Buyukatalay, Soner Birgul, Ozlem Halici, Ugur Computer Vision and Intelligent Systems Research Lab. METU Electrical and Electronics Engineering Turkey Tübitak Uzay Turkey

ISBN: (纸本)9781424456536

In this study a new algorithm for 3D surface reconstruction from multiple images using a modified photometric stereo method is proposed and tested. The new algorithm, Filtered Lambert Photometric Stereo (FLPS), determines the non-Lambert pixels in the available images using a linearity test and constructs filtering masks for each image that corresponds to specular and self or cast shadow regions. Then, the photometric stereo is applied after eliminating the points in these masks. Tests carried out on synthetic images show that LPS on filtered images is a feasible solution when more than 4 images are available.

关键词： photometric stereo Lambert reflection model filtered photometric stereo

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Exploration of the Vienna City Library Poster Collection using computer vision Approaches

Exploration of the Vienna City Library Poster Collection usi...

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2022 International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2022

作者： Kleber, Florian Novozamsky, Adam Sablatnig, Robert Dittenbach, Michael Computer Vision Lab TU Wien Vienna Austria Max. Recall Information Systems Vienna Austria

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

Parts of collections of libraries, archives, and e.g. museums can still be uncatalogued. Even if metadata is provided, only standardized information of the described resources (dependent on the collection) is available, i.e., creator names, titles, and subject terms, limiting the search options for experts and typical users. In the case of image-based collections, the information of the image itself can be used as an additional feature to extend the search capabilities of the user. This paper analyzes the use of standard computer vision methods to explore the Vienna City Library poster collection using additional image-based properties. The proposed exploration tool allows a search based on the provided metadata and features based on face detection and retrieval, image retrieval, object detection, text recognition, and main color similarity. The OpenSearch engine is used to index the metadata and visual features, allowing for a real-time search of extensive collections. The qualitative and quantitative analysis shows the potential of visual features within a search tool. © 2022 IEEE.

关键词： computer vision

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On averaging face images for recognition under pose variations

On averaging face images for recognition under pose variatio...

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作者： Zhang, Xiaozheng Zhao, Sanqiang Gao, Yongsheng Computer Vision and Image Processing Lab Institute for Integrated and Intelligent Systems Griffith University Australia

ISBN: (纸本)9781424421756

Recently, psychological studies showed that averaging human face images greatly improves the performance of face recognition under various pose, illumination, expression, and/or aging conditions. This paper investigates quantitatively the mechanism of the face averaging process in face recognition specifically against pose variations. Facilitated with 3D face dataset, the process of face averaging is tested on face images free from human errors and misalignments. Single images are chosen as gallery and the averaged views as probe in all the experiments. Three different scenarios are experimented, i.e., identification using single gallery images, identification using different gallery images, and averaging using unbalanced range of input image. The experimental results show that the averaging process under pose variations is equivalent to generating a face view in an average pose and the improvement in face recognition is subject to the conditions that the gallery pose is close to the average probe pose. © 2008 IEEE.

关键词： Face recognition

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Task modeling in imitation learning using latent variable models

Task modeling in imitation learning using latent variable mo...

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2010 10th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2010

作者： Ek, Carl Henrik Song, Dan Huebner, Kai Kragic, Danica KTH - Royal Institute of Technology Stockholm Sweden Computer Vision and Active Perception Lab. Centre for Autonomous Systems Sweden

ISBN: (纸本)9781424486885

An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations. In this paper we present a probabilistic model capable of modeling several different types of input sources within the same model. Our model is capable to infer the task using only partial observations. Further, our framework allows the robot, given partial knowledge of the scene, to reason about what information streams to acquire in order to disambiguate the state-space the most. We present results for task classification within and also reason about different features discriminative power for different classes of tasks. ©2010 IEEE.

关键词： Intelligent robots

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Unified Model for Contrast Enhancement and Denoising

Unified Model for Contrast Enhancement and Denoising

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2017 IEEE computer Society Annual Symposium on VLSI, ISVLSI 2017

作者： James, Alex Pappachen Krestinskaya, Olga Mathew, Joshin John Bioinspired Microelectronic Systems Lab Nazarbayev University Astana Kazakhstan Computer Vision Team ARS T and TT Trivandrum India

ISBN: (纸本)9781509067626

In this paper, we attempt a challenging task to unify two important complementary operations, i.e. contrast enhancement and denoising, that is required in most image processing applications. The proposed method is implemented using practical analog circuit configurations that can lead to near real-time processing capabilities useful to be integrated with vision sensors. Metrics used for performance includes estimation of Residual Noise Level (RNL), Structural Similarity Index Measure (SSIM), Output-to-Input Contrast Ratio (CRo-i), and its combined score (SCD). The class of contrast stretching methods has resulted in higher noise levels (RNL ≥ 7) along with increased contrast measures (CRo-i ≥ eight times than that of the input image) and SSIM ≤ 0.52. Denoising methods generates images with lesser noise levels (RNL ≤ 0.2308), poor contrast enhancements (CRo-i ≤ 1.31) and with best structural similarity (SSIM ≥ 0.85). In contrast, the proposed model offers best contrast stretching (CRo-i = 5.83), least noise (RNL = 0.02), a descent structural similarity (SSIM = 0.6453) and the highest combined score (SCD = 169). © 2017 IEEE.

关键词： Analog circuits

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Genetic feature subset selection for gender classification: A comparison study 6

Genetic feature subset selection for gender classification: ...

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6th IEEE Workshop on Applications of computer vision, WACV 2002

作者： Sun, Zehang Bebis, G. Yuan, Xiaojing Louis, S.J. Computer Vision Lab. Department of Computer Science University of Nevada RenoNV United States Genetic Adaptive Systems Lab. Department of Computer Science University of Nevada RenoNV United States

ISBN: (纸本)0769518583

We consider the problem of gender classification from frontal facial images using genetic feature subset selection. We argue that feature selection is an important issue in gender classification and demonstrate that Genetic Algorithms (GA) can select good subsets of features (i.e., features that encode mostly gender information), reducing the classification error. First, Principal Component Analysis (PCA) is used to represent each image as a feature vector (i.e., eigen-features) in a low-dimensional space. Genetic Algorithms (GAs) are then employed to select a subset of features from the low-dimensional representation by disregarding certain eigenvectors that do not seem to encode important gender information. Four different classifiers were compared in this study using genetic feature subset selection: a Bayes classifier, a Neural Network (NN) classifier, a Support Vector Machine (SVM) classifier, and a classifier based on Linear Discriminant Analysis (LDA). Our experimental results show a significant error rate reduction in all cases. The best performance was obtained using the SVM classifier. Using only 8.4% of the features in the complete set, the SVM classifier achieved an error rate of 4.7% from an average error rate of 8.9% using manually selected features. © 2002 IEEE.

关键词： Principal component analysis

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Probabilistic shape-based segmentation using level sets

Probabilistic shape-based segmentation using level sets

引用

2011 IEEE International Conference on computer vision Workshops, ICCV Workshops 2011

作者： Aslan, Melih S. Abdelmunim, Hossam Farag, Aly A. Computer Vision and Image Processing Lab University of Louisville Louisville KY 40299 United States Computer and Systems Engineering Department Ain Shams University Cairo Egypt

ISBN: (纸本)9781467300629

In this paper, we present a new dynamic and probabilistic shape based segmentation method using statistical and variational approaches. We use two models in this paper: i) intensity and ii) shape. In the first phase, the intensity based segmentation is done using a basic statistical level set method. In the second phase, to which we contribute, the shape model is constructed using the implicit representation of the training shapes. The resulting probability density function is used to embed the shape model into the image domain with a new energy minimization solution. Our method' s invariance to parameter initialization is evaluated through validation, and various synthetic and clinical shape registration examples are implemented. Experiments show that our proposed algorithm enhances the conventional global registration results, overcomes segmentation challenges, and is robust under various noise levels, severe occlusions, and missing parts. © 2011 IEEE.

关键词： Probability density function

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Partial generalized correlation for hyperspectral data

Partial generalized correlation for hyperspectral data

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IEEE Symposium on Computational Intelligence and Data Mining

作者： Strickert, Marc labitzke, Björn Blanz, Volker Institute of Vision and Graphics University of Siegen Germany Computer Graphics Group University of Siegen Germany Media Systems Lab University of Siegen Germany

ISBN: (纸本)9781424499274

A variational approach is proposed for the unsupervised assessment of attribute variability of high-dimensional data given a differentiable similarity measure. The key question addressed is how much each data attribute contributes to an optimum transformation of vectors for reaching maximum similarity. This question is formalized and solved in a mathematically rigorous optimization framework for each data pair of interest. Trivially, for the Euclidean metric minimization to zero distance induces highest vector similarity, but in case of the linear Pearson correlation measure the highest similarity of one is desired. During optimization the not necessarily symmetric trajectories between two vectors are recorded and analyzed in terms of attribute changes and line integral. The proposed formalism allows to assess partial covariance and correlation characteristics of data attributes for vectors being compared by any differentiable similarity measure. Its potential for generating alternative and localized views such as for contrast enhancement is demonstrated for hyperspectral images from the remote sensing domain. © 2011 IEEE.

关键词： Vectors

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A Real Time and Robust Facial Expression Recognition and Imitation approach for Affective Human-Robot Interaction Using Gabor filtering

A Real Time and Robust Facial Expression Recognition and Imi...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Cid, Felipe Prado, Jose Augusto Bustos, Pablo Nunez, Pedro Robotics and Artificial Vision Lab. Robolab Group University of Extremadura Spain Institute of Systems and Robotics Dept. Electrical and Computer Engineering University of Coimbra Portugal

ISBN: (纸本)9781467363587

Facial expressions are a rich source of communicative information about human behavior and emotion. This paper presents a real-time system for recognition and imitation of facial expressions in the context of affective Human Robot Interaction. The proposed method achieves a fast and robust facial feature extraction based on consecutively applying filters to the gradient image. An efficient Gabor filter is used, along with a set of morphological and convolutional filters to reduce the noise and the light dependence of the image acquired by the robot. Then, a set of invariant edge-based features are extracted and used as input to a Dynamic Bayesian Network classifier in order to estimate a human emotion. The output of this classifier updates a geometric robotic head model, which is used as a bridge between the human expressiveness and the robotic head. Experimental results demonstrate the accuracy and robustness of the proposed approach compared to similar systems.

关键词： Gabor filters belief networks edge detection emotion recognition face recognition feature extraction human-robot interaction image classification

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How behavior trees generalize the Teleo-Reactive paradigm and and-or-trees

How behavior trees generalize the Teleo-Reactive paradigm an...

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2016 IEEE/RSJ International Conference on Intelligent Robots and systems, IROS 2016

作者： Colledanchise, Michele Ögren, Petter Computer Vision and Active Perception Lab. Centre for Autonomous Systems School of Computer Science and Communication KTH - Royal Institute of Technology StockholmSE-100 44 Sweden

ISBN: (纸本)9781509037629

Behavior Trees (BTs) is a way of organizing the switching structure of a control system, that was originally developed in the computer gaming industry but is now also being used in robotics. The Teleo-Reactive programs (TRs) is a highly cited reactive hierarchical robot control approach suggested by Nilsson and And-Or-Trees are trees used for heuristic problems solving. In this paper, we show that BTs generalize TRs as well as And-Or-Trees, even though the two concepts are quite different. And-Or-Trees are trees of conditions, and we show that they transform into a feedback execution plan when written as a BT. TRs are hierarchical control structures, and we show how every TR can be written as a BT. Furthermore, we show that so-called Universal TRs, guaranteeing that the goal will be reached, are a special case of so-called Finite Time Successful BTs. This implies that many designs and theoretical results developed for TRs can be applied to BTs. © 2016 IEEE.

关键词： Forestry

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