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Intelligent Video Monitor System Based on Neural Networks Analysis

Intelligent Video Monitor System Based on Neural Networks An...

引用

international conference on Wireless Communications, Networking and Mobile computing (WiCom)

作者： Rong Li Li Zhu Sheng-sheng Yu College of Computer Science & Technology Huazhong University of Science and Technology China School of Electrical and Mechanical Engineering Wuhan University of Science and Engineering Wuhan China

Neural network analysis, an important branch in data mining, has been widely used in statistical analysis, pattern recognition, image processing, biological species division and customer division. Based on division method, the paper rationally selected initial class center, dynamically regulated the number of classification during image classification, and proposed an image recognition method. In the new method, multi-scale wavelet decomposition was firstly conducted for the image to be recognized. Then fisher transformation was performed on decomposition results of different scales which were defined as decomposition vectors. Finally, image recognition was realized in the fisher transformation domain according to the minimum absolute distance or comparative distance. The new method was proved to have high correct recognition rate and excellent recognition effect.

关键词： Intelligent systems Intelligent networks Monitoring Neural networks Image recognition Image analysis pattern analysis Data mining Statistical analysis pattern recognition

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Identity and variation spaces: Revisiting the fisher linear discriminant

Identity and variation spaces: Revisiting the fisher linear ...

引用

2009 IEEE 12th international conference on Computer Vision Workshops, ICCV Workshops 2009

作者： Zhang, Sheng Sim, Terence Yeh, Mei-Chen Department of Psychology University of California Santa Barbara CA United States School of Computing National University of Singapore Singapore Department of Computer Science and Information Engineering National Taiwan Normal University Taipei Taiwan

ISBN: (纸本)9781424444427

The Fisher Linear Discriminant (FLD) is commonly used in classification to find a subspace that maximally separates class patterns according to the Fisher Criterion. It was previously proven that a pre-whitening step can be used to truly optimize the Fisher Criterion. In this paper, we study the theoretical properties of the subspaces induced by this whitened FLD. Of the four subspaces induced, two are most important for classification and representation of patterns. We call these Identity Space and Variation Space. We show that only the between-class variation remains in Identity Space, and only the within-class variation remains in Variation Space. Both spaces can be used for decomposition and representation of class data. Moreover, we give sufficient conditions for these spaces to exist. Finally, we also run experiments to show how Identity and Variation Spaces may be used for classification and image synthesis. ©2009 IEEE.

关键词： pattern recognition

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pattern recognition using interval-valued intuitionistic fuzzy set and its similarity degree

Pattern recognition using interval-valued intuitionistic fuz...

引用

IEEE international conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Yingjun Zhang Peijun Ma Xiaohong Su School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424447374;9781424447541

pattern recognition under fuzzy environments is an interesting and important research topic which has been receiving more and more attention in recent years. Aiming at this kind of pattern recognition problems, fuzzy theories have been applied to the field widely and effectively. Especially interval-valued intuitionistic fuzzy sets (IVIFSs) can give not only a membership degree, but also a non-membership degree, which is more or less independent. Meanwhile the membership degree and non-membership degree are denoted by an interval which makes the IVIFSs can represent the dynamic character of features. Therefore in this paper, depending on IVIFSs and corresponding similarity degree (or distance measure) we construct a kind of novel pattern recognition approach. This approach chooses different weight for each feature according to its dissimilarity with other features. Thus the approach can show the corresponding influence and importance of different features. Finally, we utilize concrete examples to validate the proposed approach.

关键词： pattern recognition Fuzzy sets Concrete Fuzzy set theory Computer science Fuzzy systems Color Image segmentation Machine learning Medical diagnosis

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Image Segmentation - A Survey of soft computing Approaches

Image Segmentation - A Survey of Soft Computing Approaches

引用

international conference on Advances in Recent Technologies in Communication and computing, ARTCom

作者： N. Senthilkumaran R. Rajesh School of Computer Science and Engineering Bharathiar University Coimbatore India

soft computing is an emerging field that consists of complementary elements of fuzzy logic, neural computing and evolutionary computation. soft computing techniques have found wide applications. One of the most important applications is image segmentation. The process of partitioning a digital image into multiple regions or sets of pixels is called image segmentation. Segmentation is an essential step in image processing since it conditions the quality of the resulting interpretation. Lots of approaches have been proposed and a dense literature is available In order to extract as much information as possible from an environment, multicomponent images can be used. In the last decade, multicomponent images segmentation has received a great deal of attention for soft computing applications because it significantly improves the discrimination and the recognition capabilities compared with gray-level image segmentation methods. In this paper, the main aim is to understand the soft computing approach to image segmentation.

关键词： Image segmentation Fuzzy sets Entropy Pixel Genetic algorithms Fuzzy logic Application software Digital images Image processing Neural networks

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Smart sensor integration: A framework for multimodal emotion recognition in real-time

Smart sensor integration: A framework for multimodal emotion...

引用

international conference on Affective computing and Intelligent Interaction and Workshops, ACII

作者： Johannes Wagner Elisabeth André Frank Jung Multimedia Concepts and Applications University of Augsburg Augsburg Germany

Affect sensing by machines has been argued as an essential part of next-generation human-computer interaction (HCI). To this end, in the recent years a large number of studies have been conducted, which report automatic recognition of emotion as a difficult, but feasible task. However most effort has been put towards offline analysis, whereas to date only few applications exist, which are able to react to a user's emotion in real-time. In response to this deficit we introduce a framework we call Smart Sensor Integration (SSI), which considerably jump-starts the development of multimodal online emotion recognition (OER) systems. In particular SSI supports the pattern recognition pipeline by offering tailored tools for data segmentation, feature extraction, and pattern recognition, as well as, tools to apply them offline (training phase) and online (real-time recognition). Furthermore, it has been designed to handle input from various input modalities and to suit the fusion of multimodal information.

关键词： Intelligent sensors Emotion recognition pattern recognition Pipelines Feature extraction Mathematical model Computational modeling Speech Signal processing algorithms Human computer interaction

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A Hierarchical Rule-Based Activity recognition System with Frequency pattern Mining

A Hierarchical Rule-Based Activity Recognition System with F...

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international conference on Innovative computing, Information and Control (ICICIC)

作者： Ji-Yu Li Po-Cheng Huang Yau-Hwang Kuo Kuan-Rong Lee Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Department of Information Engineering Kun Shan University Tainan Taiwan

In this paper, a hierarchical system is proposed for generating personalization action and activity recognition rules. Multi-level decision rule mining approach in our system not only discovers personal habit of device using, but also finds personal pattern of devices operation manner. First, it processes non-sequential procedure, which mines user's historical action database for constructing rules to recognize actions. Second, it creates action sequence recognized by using action rules generated before. Sequential mining method is adopted to find out the most frequent sequential pattern which is seemed as personal habit of device operating manner. Finally, non-sequential rules and sequential patterns are checked to recognize user's activity. The system generates rules depending on user's habit rather than being specified by designer who only creates general rules. The simulation results reveal that the activity recognition accuracies with 10% and 20% noise interference are 87.33% and 83.33% respectively.

关键词： pattern recognition Frequency Humans Wireless sensor networks Distributed computing Image recognition Image analysis Control systems Computer science Vacuum systems

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Discriminant Isomap projection

Discriminant Isomap projection

引用

international conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Ya-Li Zheng Tai-Ping Zhang Bin Fang Yuan-Yan Tang School of Computer Science Chongqing University Chongqing China

In this paper we proposed a novel supervised dimensionality reduction method, named Discriminant Isometric projection. The aim is to compact the data points from the same cluster on high-dimension manifold to make them closer in the low-dimension space, and to make the ones from the different cluster further, which is beneficial to preserve the homogeneous characteristics for classification. We compared our method with other three methods for dimensionality reduction over the ORL face dataset and experiments show that Discriminant Isometric projection produces stable performance and good precision.

关键词： Linear discriminant analysis Principal component analysis Eigenvalues and eigenfunctions Wavelet analysis pattern analysis pattern recognition Kernel Embedded computing Face recognition Computer science

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Generic object recognition with biologically-inspired features

Generic object recognition with biologically-inspired featur...

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international conference on Bio-Inspired computing: Theories and Applications, BICTA

作者： Changxin Gao Nong Sang Jun Gao Lamei Zou Qiling Tang Institute for Pattern Recognition and Artificial intelligence Huazhong University of Science and Technology Wuhan China

In this paper, a set of biologically-inspired features are presented for robust object recognition. The proposed pyramidal feature set is obtained by extracting the geometric relationship of keypoints using a set of biologically inspired templates in different scales. Lifetime is proposed to describe the keypoints. This paper brings together new algorithms, representations, and insights which are quite generic and may well have broader applications in computer vision. The proposed approach has following properties. First, lifetime is applied to describe the stability of the keypoints. Second, the templates, which are used to extract the geometric relationships between the keypoints, are biologically inspired structure information extractors or texture information extractors. Third, the proposed approach successfully achieves an effective trade-off between generalization ability and discrimination ability for object recognition tasks. Promising experimental results on object recognition demonstrate the effectiveness of the proposed method.

关键词： Object recognition Data mining Biology Robustness Computer vision Humans Solid modeling Shape Biological system modeling pattern recognition

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Adaptive Objects Tracking by Using Statistical Features Shape Modeling and Histogram Analysis

Adaptive Objects Tracking by Using Statistical Features Shap...

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international conference on Advances in pattern recognition (ICAPR)

作者： Concetto Spampinato Department of Informatics and Telecommunication Engineering Universita Catania Catania Italy

We propose a novel method for object tracking using an adaptive algorithm based on statistical analysis of objects shape. To track objects in video sequence, we use a system that combines two algorithms: a histogram analysis algorithm and a statistical shape features modeling algorithm. The main improvement of the proposed system with respect to the others present in literature is that we do not use any a priori knowledge about how objects look like. This no a-priori model has been carried out by computing a model that takes into account the statistical behaviour of the most important objects features over the whole video frames. Moreover, an adaptive mechanism allows us to reset the statistical model creation when such a model is too much dissimilar from the real blobs features. Experiments on some real-world difficult scenarios of low resolution videos and in unconstrained environments demonstrate the very promising results achieved.

关键词： Histograms Motion detection Algorithm design and analysis Video sequences Power engineering computing Application software Active shape model pattern recognition pattern analysis Informatics

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Distributed Document Clustering for Search Engine

Distributed Document Clustering for Search Engine

引用

international conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Chang Liu Song-Nian Yu Qiang Guo School of Computer Engineering and Science Shanghai University Shanghai China

Considering that data searched from the search engine is not comprehensive, and the inconsistencies between desired results and received results are inevitable, a more effective search tool called Distributed Document Clustering for Search Engine (DDCSE) is proposed in this paper. In the DDCSE, the utilizing of distributed clustering and several search engines is used to categorize the results, in order to feedback a set of better refined results. Experiments show that a significant improvement is achieved via the distribution document clustering, so as to refine the results and reduce the time used to filter out irrelevant data for the search engines.

关键词： Search engines Data mining Distributed decision making Internet Wavelet analysis pattern analysis pattern recognition Distributed computing Clustering algorithms Data engineering

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