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

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RETRACTED ARTICLE: An adaptive SVR modeling method based on VFS for robotic grinding

RETRACTED ARTICLE: An adaptive SVR modeling method based on ...

引用

作者： Yang, Yang Song, Yixu Wang, Jiaxin Gan, Zhongxue Qi, Lizhe Dept. of Computer S and T State Key Lab of Intelligent Technology and System Tsinghua University Beijing 100084 China Research and Development Center InterSmart Robotic Systems Co. Ltd. Langfang HeBei 065001 China

ISBN: (纸本)9781424455386

The performance of a model, which is trained with offline data, is highly relied on the conditions in which the system is working. When the working conditions change, the prediction accuracy of the model will be reduced significantly. To solve this problem, we propose an adaptive SVR modeling method based on vector-field-smoothed (VFS) algorithm. This method can adapt the model quickly to new working conditions by using only a few adaptive samples. Also, it can extend the feature subspace which the model covers so as to enhance the generalization ability of the model. The experimental results show that the model using this method can achieve a much better performance than the original model, as well as the model using other adaptive SVR modeling method. © 2010 IEEE.

关键词： Robotics

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Embedded artificial gestures: Modulating behavioral coupling in human-machine interaction via motion modification

Embedded artificial gestures: Modulating behavioral coupling...

引用

IEEE International Conference on Robotics and Biomimetics

作者： De Guzman, Gonzalo C. Mistry, Ravi Tognoli, Emmanuelle Kelso, J. A. Scott Human Brain and Behavior Lab. Center for Complex Systems and Brain Sciences Florida Atlantic University Boca Raton FL 33138 United States Computer Science and Engineering Florida Atlantic University Boca Raton FL 33138 United States Intelligent Systems Research Centre University of Ulster Derry United Kingdom

ISBN: (纸本)9781424493173

With the accelerating advances in technology the need to understand human-machine interactions for the purpose of enhancing cooperative activities has become an important theoretical and empirical problem. This study uses Virtual Partner Interaction (VPI) to examine how behavioral coupling between humans and humanoid robots can be modulated through the use of embedded micro gestures or small parametric noise. VPI is a behavioral dynamic clamp constructed from established principles of live two-people interaction during performance of a coordination task. The gestures are akin to "motioning" behaviors and are in the form of parametric noise applied to either the damping or the restoring term of the oscillator dynamics of the virtual partner. To increase the probability of correctly detecting and measuring the individual performances (VP vs. subject), a conflicting task is used: subjects coordinate their rhythmic movements with the VP inphase while the VP is programmed to coordinate nominally only in antiphase. Preliminary results show that that the probability of human subjects switching to the VP's preferred pattern (anti-phase) are enhanced by parametric perturbations on either the damping or the restoring term of the VP oscillator as compared to when no perturbation is applied. The results have implication on how one may enhance human-humanoid robot coordination during performance of cooperative tasks. © 2010 IEEE.

关键词： Damping

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A reliability assessment paradigm for automated video tracking systems

A reliability assessment paradigm for automated video tracki...

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2010 20th International Conference on Pattern Recognition, ICPR 2010

作者： Chen, Chung-Hao Yao, Yi Koschan, Andreas Abidi, Mongi Department of Math and Computer Science North Carolina Central University NC 27713 United States Global Research Center General Electric NY 12309 United States Imaging Robotics and Intelligent Systems Lab. University of Tennessee Knoxville TN 37996 United States

ISBN: (纸本)9780769541099

Most existing performance evaluation methods concentrate on defining separate metrics over a wide range of conditions and generating standard benchmarking video sequences for examining the effectiveness of video tracking systems. In other words, these methods attempt to design a robustness margin or factor for the system. These methods are deterministic in which a robustness factor, for example, 2 or 3 times the expected number of subjects to track or the strength of illumination would be required in the design. This often results in overdesign, thus increasing costs, or underdesign causing failure by unanticipated factors. In order to overcome these limitations, we propose in this paper an alternative framework to analyze the physics of the failure process and, through the concept of reliability, determine the time to failure in automated video tracking systems. The benefit of our proposed framework is that we can provide a unified and statistical index to evaluate the performance of automated video tracking system for a task to be performed. At the same time, the uncertainty problem about a failure process, which may be caused by the system's complexity, imprecise measurements of the relevant physical constants and variables, or the indeterminate nature of future events, can be addressed accordingly based on our proposed framework. © 2010 IEEE.

关键词： Benchmarking

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Probabilistic models for supervised dictionary learning

Probabilistic models for supervised dictionary learning

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Conference on computer vision and Pattern Recognition (CVPR)

作者： Xiao-Chen Lian Zhiwei Li Changhu Wang Bao-Liang Lu Lei Zhang Department of Computer Science and Engineering Shanghai Jiaotong University China MOE-MS Key Lab for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University China Microsoft Research Asia China

Dictionary generation is a core technique of the bag-of-visual-words (BOV) models when applied to image categorization. Most of previous approaches generate dictionaries by unsupervised clustering techniques, e.g. k-means. However, the features obtained by such kind of dictionaries may not be optimal for image classification. In this paper, we propose a probabilistic model for supervised dictionary learning (SDLM) which seamlessly combines an unsupervised model (a Gaussian Mixture Model) and a supervised model (a logistic regression model) in a probabilistic framework. In the model, image category information directly affects the generation of a dictionary. A dictionary obtained by this approach is a trade-off between minimization of distortions of clusters and maximization of discriminative power of image-wise representations, i.e. histogram representations of images. We further extend the model to incorporate spatial information during the dictionary learning process in a spatial pyramid matching like manner. We extensively evaluated the two models on various benchmark dataset and obtained promising results.

关键词： Dictionaries Kernel Support vector machines Support vector machine classification Costs Large-scale systems Europe Machine learning Image representation Principal component analysis

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Real-time iris detection

Real-time iris detection

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15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Rizon, Mohamed Yuen, Chai Tong AlMejrad, Ali Alajlan, Naif Department of Biomedical Technology King Saud University P.O. Box 10219 Riyadh 11433 Saudi Arabia Jalan Genting Kelang Setapak 53300 Kuala Lumpur Malaysia Advanced Lab for Intelligent Systems Research Department of Computer Engineering King Saud University P.O.Box 51178 Riyadh 11543 Saudi Arabia

ISBN: (纸本)9784990288044

A real-time algorithm to automatically detect human face and irises from color images has been developed. Haar cascade-based algorithm has been applied for simple and fast face detection. The face image is then converted into grayscale image. Three types of image processing techniques have been tested respectively to study its effect on the performance of iris detection algorithm. Then, iris candidates are extracted from the valley of the face region. The iris candidates are paired up and the cost of each possible pairing is computed by a combination of mathematical models. The pairing with the lowest cost is considered as iris. The algorithm has been tested by quality images from Logitech camera and noisy images from Voxx CCD camera. The proposed algorithm has achieved a success rate of 83.60% for iris detection in an open office environment. © 2010 ISAROB.

关键词： Face recognition

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Surface Reconstruction from Multiple Images Filtering Non-Lambert Regions

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

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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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Segmentation of high resolution satellite imagery based on mean shift algorithm and morphological operations

Segmentation of high resolution satellite imagery based on m...

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Image and Signal Processing for Remote Sensing XV

作者： Aytekin, Örsan Ulusoy, Ilkay Halici, Ugur Computer Vision and Intelligent Systems Research Laboratory Electrical and Electronics Eng. Dept. Middle East Technical University 06531Ankara Turkey

ISBN: (纸本)9780819477828

Data-driven unsupervised segmentation of high resolution remotely sensed images is a primary step in understanding remotely sensed images. A new fully automatic method to delineate the segments corresponding to objects in high resolution remotely sensed images is introduced. There are extensive methods proposed in the literature which are mainly concentrated on pixel level information. The proposed method combines the structural information extracted by morphological processing with feature space analysis based on mean shift algorithm. The spectral and spatial bandwidth parameters of mean shift are adaptively determined by exploiting differential morphological profile (DMP), Spectral bandwidth is determined in relation to the first maximum value of DMP at each pixel and spatial bandwidth is determined by the corresponding index in DMP. in this method there is also no need to specify initially the maximum size of the structuring element for the morphological processes. By the use of mean shift filtering, the feature space points are grouped together which are close to each other both in the range of spatial and spectral bandwidths. The proposed method is applied on panchromatic high resolution QuickBird satellite images taken from urban areas. The results we obtained appear to be effective in terms of segmentation and combining the spectral and spatial information to extract more precise and more meaningful objects compared to fixed bandwidth mean shift segmentation. © 2009 SPIE.

关键词： Pixels

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Physics-based edge evaluation for improved color constancy

Physics-based edge evaluation for improved color constancy

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2009 IEEE Conference on computer vision and Pattern Recognition, CVPR 2009

作者： Gijsenij, Arjan Gevers, Theo Weijer, Joost Van De Intelligent Systems Lab Amsterdam University of Amsterdam Science Park 107 Amsterdam Netherlands Computer Vision Center Campus Universitat Autònoma De Barcelona 08193 Bellaterra Spain

ISBN: (纸本)9781424439935

Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material and highlight edges. These different edge types may have a distinctive inf luence on the performance of the illuminant estimation. Therefore, in this paper, an extensive analysis is provided of different edge types on the performance of edge-based color constancy methods. First, an edge-based taxonomy is presented classifying edge types based on their ref lectance properties (e.g. material, shadow-geometry and highlights). Then, a performance evaluation of edge-based color constancy is provided using these different edge types. From this performance evaluation, it is derived that certain edge types are more valuable than material edges for the estimation of the illuminant. To this end, the weighted Grey-Edge algorithm is proposed in which certain valuable edge types are more emphasized for the estimation of the illuminant. From the experimental results, it is shown that the proposed weighted Grey-Edge algorithm based on the shadowshading variant, i.e. assigning higher weights to edges with more energy in the shadow-shading direction, results in the best performance. Moreover, all current state-of-theart methods, including pixel-based methods and edge-based methods, have been signif icantly outperformed by the proposed weighted Grey-Edge algorithm, resulting in an improvement of 9% over the current best-performing algorithm. © 2009 IEEE.

关键词： Color

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Approximate dynamic space warping for fast shape retrieval

Approximate dynamic space warping for fast shape retrieval

引用

2009 International Conference on Image Processing, computer vision, and Pattern Recognition, IPCV 2009

作者： Alajlan, Naif Advanced Lab. for Intelligent Systems Research Computer Engineering Dept. King Saud University P. O. Box 51178 Riyadh 11543 Saudi Arabia

ISBN: (纸本)9781601321190

Dynamic space warping (DSW) has emerged as a very effective algorithm for matching shapes. However, a central computational difficulty associated with DSW arises when a boundary's starting point (or rotation angle) is unknown. In this paper, the HopDSW algorithm is proposed to speed up the starting point computation. Rather than performing an exhaustive search for the correct starting point as in classical approaches, the proposed algorithm operates in a coarse-tonne manner. The coarse search is global and uses a hopping step to exclude points from the search. Then, the search is refined in the neighborhood of the solution of the coarse search. A criterion that governs selecting the hopping step parameter is given, which reduces the number of starting point computations by an order. For shape representation, triangle area signature (TAS) is computed from triangles formed by the boundary points. Experimental results on the MPEG-7 CE-1 database of 1400 shapes show that the proposed algorithm returns the solution of the exhaustive search with a high degree of accuracy and a considerable reduction in the number of computations.

关键词： Motion Picture Experts Group standards

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Surface reconstruction from multiple images filtering non-Lambert regions

Surface reconstruction from multiple images filtering non-La...

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IEEE International Conference on Image Processing

作者： Soner Büyükatalay Özlem Birgül Uğur Halici METU Electrical and Electronics Engineering Computer Vision and Intelligent Systems Research Laboratory Turkey TÜbitak Uzay Turkey

关键词： Surface reconstruction Image reconstruction Filtering Optical reflection Light sources Photometry Testing Vectors Lighting Stereo vision

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