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Derivations of normalized mutual information in binary classifications

Derivations of normalized mutual information in binary class...

引用

6th international conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Wang, Yong Hu, Bao-Gang Beijing Graduate School Chinese Academy of Sciences Beijing 100049 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769537351

Although the conventional performance indexes, such as accuracy, are commonly used in classifier selection or evaluation, information-based criteria, such as mutual information, are becoming popular in feature/model selections. In this work, we analyze the classifier learning model with the maximization normalized mutual information (NI) criterion, which is novel and well defined in a compact range for classifier evaluation. We derive close-form relations of normalized mutual information with respect to accuracy, precision, and recall in binary classifications. By exploring the relations among them, we reveal that NI is actually a set of nonlinear functions, with a concordant power-exponent form, to each performance index. the relations can also be expressed with respect to precision and recall, or to false alarm and hitting rate (recall). © 2009 IEEE.

关键词： Function evaluation

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A General Learning Method for Automatic Title Extraction from HTML Pages

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6th international conference on Machine Learning and Data Mining in pattern recognition

作者： Changuel, Sahar Labroche, Nicolas Bouchon-Meunier, Bernadette LIP6 DAPA F-75016 Paris France

ISBN: (纸本)9783642030697

this paper addresses the problem of automatically learning the title metadata from HTML documents. the objective, is to help indexing Web resources that are poorly annotated. Other works proposed similar objectives, but they considered only titles in text format . In this paper we propose a general learning schema that allows learning textual titles based on style information and image format titles based on image properties. We construct features from automatically annotated pages harvested from the Web;this paper details the corpus creation method as well as the information extraction techniques. Based oil these features. learning algorithms, such as Decision Trees and Random Forest algorithms are applied achieving good results despite the heterogeneity of our corpus, we also show that, combining both methods can induce better performance.

关键词： Decision trees

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Ubiquitous Intelligence and Computing - 6th international conference, UIC 2009, Proceedings

Ubiquitous Intelligence and Computing - 6th International Co...

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6th international conference on Ubiquitous Intelligence and Computing, UIC 2009

ISBN: (纸本)3642028292

the proceedings contain 28 papers. the topics discussed include: distributed computing in opportunistic environments;web of things as a framework for ubiquitous intelligence and computing;context-aware activity recognition through a combination of ontological and statistical reasoning;context-aware path planning in ubiquitous network;a framework to calibrate a MEMS sensor network;application domain driven data visualization framework for wireless sensor networks;hybrid Bluetooth scatter net routing;self-estimation of neighborhood density for mobile wireless nodes;NavTag: an inter-working framework based on tags for symbolic location coordinates for smart spaces;conflicting-set-based wormhole attack resistant localization in wireless sensor networks;novel and efficient identity-based authenticated key agreement protocols from weil pairings;implicit user re-authentication for mobile devices;lattice based privacy negotiation rule generation for context-aware service;and anticipative wrap-around inquiry method towards efficient RFID tag identification.

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Modeling of Elastic Behavior of 3D Deformable Objects from Range and Tactile Imaging

Modeling of Elastic Behavior of 3D Deformable Objects from R...

引用

6th international conference on Image Analysis and recognition

作者： Cretu, Ana-Maria Payeur, Pierre Petriu, Emil M. Univ Ottawa SITE Ottawa ON K1N 6N5 Canada

ISBN: (纸本)9783642026102

the paper presents a joint sensing strategy that combines tactile probing and range imaging for the mapping of the elastic properties that characterize 3D deformable objects. A feedforward neural network architecture is employed in an original manner to model the complex relationship between the surface deformation and the forces exemplified in non-rigid bodies. Experimental results are presented for objects made of materials with different elastic behaviors and for their different deformation stages.

关键词： Deformable objects elastic behavior range imaging tactile probing neural networks

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Real-time Accurate Facial Feature Corner Localization by Rule-Based Selection

Real-time Accurate Facial Feature Corner Localization by Rul...

引用

6th international conference on Computer Graphics, Imaging and Visualization (CGIV 2009)

作者： Tong, Jiaqi Ma, Lizhuang Xu, Zhiliang Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200030 Peoples R China

ISBN: (纸本)9780769537894

We propose a coarse-to-fine approach for localizing eye and lip corners, which is accurate and robust, and can be executed in real-time. Given an image, we first detect the face and the rough initial positions of eyes and lip in the coarsest level. In the middle level, SUSAN corner detection is applied to obtain candidate corners, from which we select a best one as the facial feature corner. Finally, in the finest level, the corner is further refined by Normalized Cross-Correlation (NCC) template matching. We have tested our algorithm on the database containing over 5000 faces with various poses, expressions, occlusions and light conditions. the experimental results show that our method can successfully localize the facial feature corners with more than 20FPS, which is very appealing.

关键词： pattern recognition Facial features localization SUSAN corner detection Coarse to fine framework

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3D Shape from Focus and Depth Map Computation Using Steerable Filters

3D Shape from Focus and Depth Map Computation Using Steerabl...

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6th international conference on Image Analysis and recognition

作者： Minhas, Rashid Mohammed, Abdul A. Wu, Q. M. Jonathan Sid-Ahmed, Maher A. Univ Windsor Dept Elect & Comp Engn Windsor ON N9B 3P4 Canada

ISBN: (纸本)9783642026102

the technique utilized to retrieve spatial information from a sequence of images with varying focus plane is termed as shape from focus (SFF). Traditional SFF techniques perform inadequately due to their inability to deal with images that contain high contrast variations between different regions, shadows, defocused points, noise, and oriented edges. A novel technique to compute SFF and depth map is proposed using steerable filters. Steerable filters, designed in quadrature pairs for better control over phase and orientation, have successfully been applied in many image analysis and pattern recognition schemes. Steerable filters represent architecture to synthesize filters of arbitrary orientation using linear combination of basis filters. Such synthesis is used to determine analytically the filter Output as a function of orientation. SFF is computed using steerable filters on variety of image sequences. Quantitative and qualitative performance analyses validate enhanced performance of our proposed scheme.

关键词： pattern recognition

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pattern Mining with Natural Language Processing: An Exploratory Approach

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6th international conference on Machine Learning and Data Mining in pattern recognition

作者： Mendes, Ana Cristina Antunes, Claudia Univ Tecn Lisboa Inst Super Tecn Spoken Language Syst Lab INESC ID L2F R Alves Redol 9-2 P-1000029 Lisbon Portugal Univ Tecn Lisboa Dept Comp Sci & Engn Inst Super Tecn P-1049001 Lisbon Portugal

ISBN: (纸本)9783642030697

pattern mining derives from the need of discovering hidden knowledge in very large amounts of data, regardless form in which it is presented. When it;comes to Natural Language, Processing (NLP), it arose along the humans necessity of being understood by computers. In this paper we present, an exploratory approach that aims at bringing together the best of both worlds. Our goal is to patterns in linguistically processed texts, through the usage of NLP state-of-the-art tools and traditional pattern mining algorithms. Articles from a Portuguese newspaper are the input of a series of tests described in this paper. First, they are processed by an NLP chain which performs a (feel) linguistic analysis of text: afterwards pattern mining algorithms Apriori and GenPrefixSpan, are used. Results showed the applicability of sequential pattern mining techniques in textual structured data and also provided Several evidence's about the structure of the language.

关键词： Data mining

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Analysis of Human Gait Bilateral Symmetry for Functional Assessment after an Orthopaedic Surgery

Analysis of Human Gait Bilateral Symmetry for Functional Ass...

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6th international conference on Image Analysis and recognition

作者： Xu, Ying Bo Wang, Chun Hao Zalzal, Paul Safir, Oleg Guan, Ling Ryerson Univ Dept Elect & Comp Engn 350 Victoria St Toronto ON Canada McMaster Univ Dept Surg Hamilton ON L8S 4L8 Canada Mt Sinai Hosp Toronto ON Canada

ISBN: (纸本)9783642026102

We proposed a color marker based computer vision system which can provide temporal-spatial and kinematic information of human gait. this system provides quantitative gait pattern information for clinicians to evaluate the rehabilitation progress of the patients who had undertaken total knee replacement (TKR) and/or total hip replacement (thR) Surgeries. the symmetry between left leg and right leg is a very useful feature for this evaluation purpose. To calculate this parameter, we introduced a new curve feature to describe the gait pattern. this Curve feature serves as people's walking signature. the symmetry is denoted by dynamic time warping (DTW) distance of this walking signature. through experiments, we demonstrate the effectiveness of the proposed system.

关键词： gait pattern symmetry dynamic time warping

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Speedup the Multi-Camera Video-Surveillance System for Elder Falling Detection

Speedup the Multi-Camera Video-Surveillance System for Elder...

引用

6th international conference on Embedded Software and Systems

作者： Shieh, Wann-Yun Huang, Ju-Chin Department of Computer Science and Information Engineering Chang Gung University Taiwan

ISBN: (纸本)9780769536781

Nowadays, all countries have to face the growing populations of elders. For most elders, unpredictable falling accidents may occur at the corner of stairs or a long corridor due to body functional decay. If we delay to rescue a falling elder who is likely fainting, more serious consequent injury may happen. Traditional secure or video surveillance systems need someone to monitor a centralized screen continuously, or need an elder to wear sensors to detect accidental falling signals, which explicitly require higher costs of care staffs or cause inconvenience for an elder. In this work, we propose a human-shape-based falling detection algorithm and implement this algorithm in a multi-camera video surveillance system. the algorithm uses multiple cameras to fetch the images from different regions required to monitor. It then uses a filling-pattern recognition approach to determine fan accidental falling has occurred If yes, the system will send short messages to someone needs to alert. In addition, we propose a multi-video-stream processing algorithm to speedup the throughput for the video surveillance system having multiple cameras. We partition the workloads of each video-surveillance streaming into four tasks: image fetch, image processing, human-shape generation, and pattern recognition. Each task will be handled by a forked thread. When the system receives multiple video streams from cameras, there are four simultaneous threads executed for different tasks. the objective of this algorithm is to exploit large thread-level-parallelism among those video-stream operations, and apply pipelining technique to execute these threads. All above algorithms have been implemented in a real-world environment for functionality proof. We also measure the system performance after multi-streaming speedup. the results show that the throughput can be improved by about 2.12 times for a four-camera surveillance system.

关键词： Falling detection pattern recognition pipelining multithread video surveillance multiple cameras

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Local Triplet pattern for Content-Based Image Retrieval

Local Triplet Pattern for Content-Based Image Retrieval

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6th international conference on Image Analysis and recognition

作者： He, Daan Cercone, Nick Dalhousie Univ Fac Comp Sci Halifax NS Canada York Univ Fac Sci & Engn N York ON M3J 1P3 Canada

ISBN: (纸本)9783642026102

An image feature named Local Triplet pattern (LTP) is proposed for image retrieval applications. the LTP feature of an image is it histogram which contains spatial information among neighboring pixels in the image. An LTP level is extracted front each 3 x 3 pixel block. the color levels of the eight surrounding pixels are compared with the color level of the center pixel. the comparison returns one of the triplet codes: 0, 1, or 2 to represent the three conditions: the color level of a neighboring pixel is smaller than, equal to, or larger than the color level of the center pixel. the eight triplet codes from the eight surrounding pixels are then transformed to an LTP level. We also consider extracting the LTP from it quantized color space and at different pattern length according to the application needs. Experimental results show that our proposed LTP histogram consistently outperforms other histograms with spatial information oil both the texture and generic image datasets.

关键词： Pixels

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