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International Conference on computer science and Software Engineering, CSSE 2008

作者： Hualong, Zhao Hongshi, Sang Tianxu, Zhang Yebin, Fan State Key Lab. for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769533360

Two of the most significant factors in the success of today's system-on-chip (SoC) designs are the ability to deliver efficient access to off-chip high speed memory and the ability to be compatible with several different interface-timings of several different sorts of memories. And the scheduling scheme of data streams for multi-master and multi-outstanding requests situation in complex SoC should be considered carefully, too. This paper introduces a novel general external memory interface (GEMI) architecture for the high performance and high flexibility memory interface. Several techniques and methods, i.e. data and command buffers based on asynchronous FIFO, optimized bank management, multi-port access scheduler, request reorder unit, are proposed in this paper for fulfilling the requirements mentioned above. Some techniques are specially proposed for data streams scheduling in complex SoC. At the end of the paper, the simulation and tape-out results are provided. The whole implementation of architecture is proven to be not only functional and efficient, but also flexible and reusable by simulation and silicon verification. © 2008 IEEE.

关键词： Scheduling

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MLPP: A modified version of locality preserving projection

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Journal of Computational Information Systems 2008年第5期4卷 1891-1896页

作者： Zheng, Zhonglong Zhang, Haoran Yang, Fa Yang, Jie Department of Computer Science Zhejiang Normal University Jinhua 321004 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

Locality Preserving Projection (LPP), as a linear manifold learning algorithm, has attracted much interests in recent years. LPP considers an n1× n2image as a vector in €n1×n2space, and thus is limited by the curse of dimensionality. To deal with such problem, Principal Component Analysis (PCA) is traditionally used for dimensionality reduction first. However, some discriminant information would be discarded by PCA. In this paper, a modified version of LPP (MLPP) is proposed which can be applied directly in the original face space without the aid of PCA. Moreover, the mapping matrix derived from MLPP is orthogonal in contrast to that of LPP. Experiments show competitive performance of our method. © 2008 Binary Information Press.

关键词： Principal component analysis

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Grouping edge points into line segments by sequential Hough transformation

Grouping edge points into line segments by sequential Hough ...

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International Conference on pattern recognition

作者： Xiaofeng Zhang H. Burkhardt Chair of Pattern Recognition and Image Processing Department of Computer Science University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769507506

An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region to which the edge points are supposed to be mapped is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation for detecting peaks one by one in the parameter domain is implemented, and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both the generated edges disturbed by different noise levels and real images taken from an indoor environment.

关键词： image segmentation image edge detection Indoor environments Face detection pattern recognition image processing computer science Noise robustness Noise level Noise measurement

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Face recognition - A one-shot learning perspective 15

Face recognition - A one-shot learning perspective

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15th International Conference on Signal image Technology and Internet Based Systems, SISITS 2019

作者： Chanda, Sukalpa Gv, Asish Chakrapani Brun, Anders Hast, Anders Pal, Umapada Doermann, David Department of Information Technology Østfold University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Centre for Image Analysis Uppsala University Sweden Computer Science and Engineering University at Buffalo United States

ISBN: (纸本)9781728156866

Ability to learn from a single instance is something unique to the human species and One-shot learning algorithms try to mimic this special capability. On the other hand, despite the fantastic performance of Deep Learning-based methods on various image classification problems, performance often depends having on a huge number of annotated training samples per class. This fact is certainly a hindrance in deploying deep neural network-based systems in many real-life applications like face recognition. Furthermore, an addition of a new class to the system will require the need to re-train the whole system from scratch. Nevertheless, the prowess of deep learned features could also not be ignored. This research aims to combine the best of deep learned features with a traditional One-Shot learning framework. Results obtained on 2 publicly available datasets are very encouraging achieving over 90% accuracy on 5-way One-Shot tasks, and 84% on 50-way One-Shot problems. © 2019 IEEE.

关键词： Face recognition

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Head detection and localization from sparse 3D data

Head detection and localization from sparse 3D data

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24th German Association for pattern recognition Symposium, DAGM 2002

作者： Clabian, Markus Rötzer, Harald Bischof, Horst Kropatsch, Walter Advanced Computer Vision GmbH Donau City Str.1 ViennaA-1220 Austria Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria

ISBN: (纸本)354044209X

Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19x19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images. © Springer-Verlag Berlin Heidelberg 2002.

关键词： computers

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Modeling and tracking of dynamic obstacles for logistic plants using omnidirectional stereo vision

Modeling and tracking of dynamic obstacles for logistic plan...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： A. Vatavu A. D. Costea S. Nedevschi Computer Science Department Technical University of Cluj-Napoca Image Processing and Pattern Recognition Research Center Romania

In this work we present an obstacle detection and tracking solution applied to Automated Guided Vehicles (AGVs) in industrial environments. The proposed method relies on information provided by an omnidirectional stereo vision system enabling 360 degree perception around the AGV. The stereo data is transformed into a classified digital elevation map (DEM). Based on this intermediate representation we are able to generate a set of obstacle hypotheses, each represented by a 3D cuboid and a free-form polygonal model. The cuboidal model is used for the classification of each hypothesis as "Pedestrian", "AGV", "Large Obstacle" or "Small Obstacle", while the free-form polylines are used for object motion estimation relying on an Iterative Closest Point (ICP) method. The obtained measurements are subjected to a Kalman filter based tracking approach, in which the data association takes into account also the classification results.

关键词： Three-dimensional displays Logistics Stereo vision Cameras Tracking Computational modeling Visualization

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Fast Pedestrian Detection for Mobile Devices

Fast Pedestrian Detection for Mobile Devices

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International IEEE Conference on Intelligent Transportation Systems

作者： Arthur Daniel Costea Andreea Valeria Vesa Sergiu Nedevschi Image Processing and Pattern Recognition Research Center Computer Science Department Technical University of Cluj-Napoca Romania

ISBN: (纸本)9781467365970

In this paper we present a fast and robust solution for pedestrian detection that can run in real time conditions even on mobile devices with limited computational power. An optimization of the channel features based multiscale detection schemes is proposed by using 8 detection models for each half octave scales. The image features have to be computed only once each half octave and there is no need for feature approximation. We use multiscale square features for training the multiresolution pedestrian classifiers. The proposed solution achieves state of art detection results on Caltech pedestrian benchmark at over 100 FPS using a CPU implementation, being the fastest detection approach on the benchmark. The solution is fast enough to perform under real time conditions on mobile platforms, yet preserving its robustness. The full detection process can run at over 20 FPS on a quad-core ARM CPU based smartphone or tablet, being a suitable solution for limited computational power mobile devices or embedded platforms.

关键词： pedestrian detection image features solution image feature Mobile devices Pedestrians Solutions Fasting Robust solution FES gene Smartphone Solution computational power

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Performing clustering analysis on collaborative models

Performing clustering analysis on collaborative models

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作者： Shen, Hongbin Yang, Jie Chen, Ningjiang Dong, Yifei Wang, Shitong Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Philips Research East Asia Shanghai 200070 China School of Computer Science and Engineering University of New South Wales Australia Department of Information Science Southern Yangtze University Wuxi Jiangsu 214036 China

Conventional clustering algorithms are designed for a single independent dataset, i.e. Fuzzy C-Means (FCM) clustering algorithm. In the real world, a dataset is independent of other datasets but sometimes can be cooperative with others by exchanging information, such as the relationship between subsidiary companies. We should therefore consider the influence from other relative collaborative datasets while performing clustering learning under such collaborative circumstances. In this paper, three different collaborative models are discussed and new correct methods are proposed to quantitatively measure such collaboration between datasets, i.e. information gain. The corresponding collaborative clustering algorithms are presented accordingly and the theoretical analysis shows that the new cooperative clustering algorithms can finally converge to a local minimum. Experimental results demonstrate that the clustering structures obtained by new cooperative algorithms are different from those of conventional algorithms for the consideration of collaboration and the performances of these collaborative clustering algorithms can be much better than those conventional single clustering algorithms under the cooperating circumstances. ©?2005-IOS Press and the authors. All rights reserved.

关键词： Clustering algorithms

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Spatial Direction Estimation for Multiple Sound Sources in reverberation environment

Spatial Direction Estimation for Multiple Sound Sources in r...

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IEEE International Conference on Robotics and Biomimetics

作者： Huakang Li Qunfei Zhao Akira Saji Keita Tanno Jie Huang School of Computer Science and Engineering University of Aizu Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

ISBN: (纸本)9781424493197

In this paper, we propose spatial localization of multiple sound sources using a spherical robot head equipped with four microphones. We obtain arrival time differences using phase difference candidates. Based on the model of precedence effect, arrival temporal disparities obtained from the zero-crossing point are used to calculate time differences and suppress the influence of echoes in a reverberant environment. To integrate spatial cues of different microphone pairs, we use a mapping method from the correlation between different microphone pairs to a 3D map corresponding to azimuth and elevation of sound sources directions. Experiments indicate that the system provides the distribution of sound sources in azimuth-elevation localization, with the EA model even concurrently in reverberant environments.

关键词： Microphones Azimuth Estimation Histograms Reverberation Robot sensing systems

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Evaluation of diffusion techniques for improved vessel visualization and quantification in three-dimensional rotational angiography 4th

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4th International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 2001

作者： Meijering, Erik Niessen, Wiro Weickert, Joachim Viergever, Max Image Sciences Institute University Medical Center Utrecht Heidelberglaan 100 UtrechtNL-3584 CX Netherlands Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim MannheimD-68131 Germany

ISBN: (纸本)3540426973

Three-dimensional rotational angiography (3DRA) is a promising imaging technique which yields high-resolution isotropic 3D images of vascular structures. Raw 3DRA images, however, usually suffer from a high noise level and the presence of other artifacts. For accurate visualization and quantification of vascular anomalies, noise reduction is therefore highly desirable. In this paper we analyze the effects of several linear and nonlinear filtering techniques for that purpose. From the results of in vitro experiments we conclude that edge-enhancing anisotropic diffusion is very suitable for mentioned tasks. However, in view of the computational requirements of this technique, the regularized isotropic nonlinear diffusion scheme may be considered a useful alternative. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Diffusion

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