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IEEE International Conference on robotics and Biomimetics

作者： Sebastian Bartsch Frank Kirchner Department of Mathematics and Computer Science Robotics Lab University of Brethemen Bremen Germany Department of Mathematics and Computer Science Robotics Lab and German Research Center for Artificial Intelligence Robotic Lab University of Brethemen Bremen Germany

This paper presents a biologically inspired control approach for the locomotion of humanoid robots based on a central pattern generator concept with additional balancing behavior which was tested on BIN-HUR, a modified Kondo KHR-1 robot equipped with a custom-made micro-controller board. The software concept is built up on a new behavior-based microkernel named Monster.

关键词： Robust control Humanoid robots Feedback Frequency Legged locomotion Servomechanisms Pulse width modulation Intelligent sensors Leg Test pattern generators

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Towards Face Recognition at a Distance

Towards Face Recognition at a Distance

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2006 IET Conference on Crime and Security

作者： Simon J.D. Prince James Elder Y. Hou M. Sizinstev E. Olevskiy Department of Computer Science University College London UK Center for Vision Research York University Toronto Canada

Current face recognition algorithms require the tacit cooperation of users, who must position themselves in a small area of space and face the camera. Face recognition in uncontrolled conditions, such as in security camera footage presents two extra challenges. First, it is difficult to capture good quality images of faces in this setting. Second, the pose of the face is relatively uncontrolled which causes most face recognition algorithms to fail. In this paper, we present a series of solutions to address these problems. High quality face images are captured using a foveated wide field sensor, in which a narrow-field camera is directed towards faces using information from a static wide-field camera. Feature points corresponding to the eyes/nose etc. are accurately localized and face shape is normalized. A novel algorithm is introduced to identify these (typically non-frontal) faces from a test gallery of frontal faces. Results are demonstrated to be superior to contemporary approaches

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A visual servoing approach for tracking features in urban areas using an autonomous helicopter

A visual servoing approach for tracking features in urban ar...

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IEEE International Conference on robotics and Automation (ICRA)

作者： L. Mejias P. Campoy S. Saripalli G.S. Sukhatme Computer Vision Group Universidad Politécnica de Madrid Madrid Spain Robotic Embedded Systems Laboratory Center for Robotics and Embedded Systems Department of Computer Science University of Southern California Los Angeles CA USA

The use of unmanned aerial vehicles (UAVs) in civilian and domestic applications is highly demanding, requiring a high-level of capability from the vehicles. This work addresses the design and implementation of a vision-based feature tracker for an autonomous helicopter. Using vision in the control loop allows estimating the position and velocity of a set of features with respect to the helicopter. The helicopter is then autonomously guided to track these features (in this case windows in an urban environment) in real time. The results obtained from flight trials in a real world scenario demonstrate that the algorithm for tracking features in an urban environment, used for visual servoing of an autonomous helicopter is reliable and robust

关键词： Visual servoing Urban areas Helicopters Aircraft navigation Machine vision Control systems Unmanned aerial vehicles Global Positioning System computer vision Robot vision systems

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Learning predictive state representations using non-blind policies 06

Learning predictive state representations using non-blind po...

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ICML 2006: 23rd International Conference on Machine Learning

作者： Bowling, Michael McCracken, Peter James, Michael Neufeld, James Wilkinson, Dana Department of Computing Science University of Alberta Edmonton Alta. T6G 2E8 Canada AI and Robotics Group Technical Research Dept. Toyota Technical Center Ann Arbor MI United States School of Computer Science University of Waterloo Waterloo Ont. Canada

ISBN: (纸本)1595933832

Predictive state representations (PSRs) are powerful models of non-Markovian decision processes that differ from traditional models (e.g., HMMs, POMDPs) by representing state using only observable quantities. Because of this, PSRs can be learned solely using data from interaction with the process. The majority of existing techniques, though, explicitly or implicitly require that this data be gathered using a blind policy, where actions are selected independently of preceding observations. This is a severe limitation for practical learning of PSRs. We present two methods for fixing this limitation in most of the existing PSR algorithms: one when the policy is known and one when it is not. We then present an efficient optimization for computing good exploration policies to be used when learning a PSR. The exploration policies, which are not blind, significantly lower the amount of data needed to build an accurate model, thus demonstrating the importance of non-blind policies.

关键词： Predictive control systems

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Wide Dynamic Range vision for Robot Eyes based on Double Capturing Scheme

Wide Dynamic Range Vision for Robot Eyes based on Double Cap...

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IEEE SENSORS

作者： Sung-Kee Park Jin Heon Kim Intelligent Robotics Research Center Korea Institute of Science and Technology Seoul South Korea Department of Computer Engineering Seokyeong University Seoul South Korea

A new method of combining double captured images to extend dynamic range is proposed in this paper. Two images taken with long and short exposure times respectively are combined by proposed DSPA (difference & slant based pixel adjustment) algorithm, dynamically varying weighted averaging scheme to present a scene of wide dynamic range. Compared with the previous works using multiple capturing, our approach captures only twice to facilitate practical implementation. It is characterized by simple arithmetic operations which can be easily implemented by a small H/W. Compared with the previous double capturing scheme, it shows enhanced contrast which contains more edge information, easy control of resultant effects while still retaining simple architectural merit. The test results for the several scenes show it has logarithmic convergence characteristics and more edge quantity compared to the previous works.

关键词： Dynamic range Robot vision systems Eyes Layout Intelligent robots Cameras Intelligent sensors Robot sensing systems Pixel Charge coupled devices

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Multi-subregion-based probabilistic approach to pose-invariant face recognition

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Systems and computers in Japan 2006年第8期37卷 68-76页

作者： Yamada, Akihiko Kanade, Takeo SANYO Electric Co. Ltd. R and D Headquarters Osaka 573-8534 Japan Robotics Institute Carnegie Mellon University Pittsburgh PA 15213 Human Ecology Research Center Department of Computer Science and Robotics Carnegie Mellon University

Current automatic facial recognition systems are not robust to changes in illumination, pose, facial expression, and occlusion. In this paper, in order to address the problem of pose change, we propose an algorithm based on a probabilistic approach to face recognition that takes into account the pose difference between probe and gallery images. By using a large facial image database, the CMU PIE database, which contains images of the same set of people taken from many different angles, we have developed a probabilistic model of how facial features change as the pose changes. This model enables us to make our face recognition system more robust to changes of pose in the probe image. The experimental results show that this approach achieves a better recognition rate than conventional face recognition methods over a much larger range of poses. For example, when the gallery contains only images of a frontal face and the probe image varies its pose orientation, the recognition rate shows less than a 10% difference until the probe pose begins to differ by more than 45°, whereas the recognition rate of a PCA-based method begins to drop at differences as small as 10°, and that of a representative commercial system begins to drop at 30°. © 2006 Wiley Periodicals, Inc.

关键词： Face recognition

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An adaptive neuro-fuzzy system for color image segmentation

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Journal of the Indian Institute of science 2006年第5期86卷 493-506页

作者： Deshmukh, Kanchan Shinde, G.N. M.G.M's College of Computer Science and Information Technology Near Airport Nanded 431 605 India Y.M. Research Center VIP Road Nanded 431 605 India Department of Electronics Computer Vision Lab. Indian Institute of Technology Kharagpur 721 302 India C/o Amit V. Nandedkar H. No. 49. 'Sheshsmuruti' Ashok Nagar Nanded 431 605 India

Image segmentation and object extraction plays an important role in image analysis and computer vision. In this paper, we propose a novel technique for color image segmentation called 'adaptive neuro-fuzzy color image segmentation (ANFCIS)'. The proposed system consists of multilayer perception (MLP)-like network which performs color image segmentation using multilevel thresholding. Threshold values for detecting clusters and their labels are found automatically using fuzzy C-means (FCM) clustering technique. Fuzzy entropy is used as a tool to decide the number of clusters. ANFCIS uses saturation and intensity planes of HSV (hue, saturation, intensity) color space for segmentation. Neural network is employed to find the number of objects automatically from an image. The major advantage of this method is that it does not require a priori knowledge to segment a color image. The algorithm is found to be robust and relatively computationally inexpensive for large variety of color images. Experimental results have demonstrated the effectiveness and efficiency of the proposed method. © Indian Institute of science.

关键词： Image segmentation

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Semi-Automatic Lymph Node Segmentation in LN-MRI

Semi-Automatic Lymph Node Segmentation in LN-MRI

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IEEE International Conference on Image Processing

作者： G. Unal G. Slabaugh A. Ess A. Yezzi T. Fang J. Tyan M. Requardt R. Krieg R. Seethamraju M. Harisinghani R. Weissleder Siemens Corporate Research Intelligent Vision and Reasoning Princeton NJ USA Computer Science Department Swiss Federal Institute of Technology Zurich Switzerland School of ECE Georgia Institute of Technology Atlanta GA USA Siemens Med-MIR Medical Solutions Erlangen Germany Siemens Medical Solutions Med-MR Malvern PA USA Center For Molecular Imaging Research Massachusetts General Hospital Harvard University Boston MA USA

Accurate staging of nodal cancer still relies on surgical exploration because many primary malignancies spread via lymphatic dissemination. The purpose of this study was to utilize nanoparticle-enhanced lymphotropic magnetic resonance imaging (LN-MRI) to explore semi-automated noninvasive nodal cancer staging. We present a joint image segmentation and registration approach, which makes use of the problem specific information to increase the robustness of the algorithm to noise and weak contrast often observed in medical imaging applications. The effectiveness of the approach is demonstrated with a given lymph node segmentation problem in post-contrast pelvic MRI sequences.

关键词： Lymph nodes Image segmentation Biomedical imaging Medical diagnostic imaging Cancer Feature extraction Magnetic resonance imaging Shape Oncological surgery Nanoparticles

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Authenticating corrupted facial images on stand-alone DSP system

Authenticating corrupted facial images on stand-alone DSP sy...

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5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005

作者： Lee, Sang-Woong Jung, Ho-Choul Lee, Seong-Whan Center for Artificial Vision Research Department of Computer Science and Engineering Korea University Anam-dong Seongbuk-ku Seoul 136-713 Korea Republic of

In this paper, we propose a method of authenticating corrupted photo images based on noise parameter estimation and implement an authentication system using TMS320C6711 DSP chip. The proposed method first generates corrupted images and the noise parameters in the training phase. With a corrupted image and an original image, the noise parameters of the corrupted photo image can be estimated in the testing phase. Finally, we can make a synthesized photo image from the original photo image using the estimated noise parameters. We made some experiments on the prototype of the stand-alone system to verify the performance of the proposed method and to apply for real-life applications. The experimental results on this system show that the proposed method can estimate the noise parameters accurately and improve the performance of photo image authentication. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Face recognition

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Illumination invariant face recognition using linear combination of face exemplars

Illumination invariant face recognition using linear combina...

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5th International Conference on Audio - and Video-Based Biometric Person Authentication, AVBPA 2005

作者： Moon, Song-Hyang Lee, Sang-Woong Lee, Seong-Whan Center for Artificial Vision Research Department of Computer Science and Engineering Korea University Anam-dong Seongbuk-ku Seoul 136-713 Korea Republic of

Facial appearance changes induced by lighting variation cause serious performance degradation in face recognition. Current face recognition systems encounter the difficulty to recognize faces under arbitrary illuminations. In this paper, we propose a new face recognition method under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the exemplars which are synthesized from photometric stereo images of training data and the linear combination of those exemplars are used to represent the new face. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute Face Database. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Face recognition

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