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International Conference on Ubiquitous Intelligence & Computing

作者： Jun-Horng Chen Teng-Hui Tseng Chin-Lun Lai Sheng-Ta Hsieh Oriental Institute of Technology Department of Communication Engineering

ISBN: (纸本)9781467330848

This work proposes an intelligent and interactive virtual fence system for security management in a danger- or accident-prone area. The proposed system is designed to be realized in an outdoor and wide-area park. With the proposed system, users can visually and arbitrarily define the polygonic alert area for the sake of security. The Gaussian Mixture Model (GMM) and adaboost algorithms are modified and integrated in this work to provide a robust human detection. As soon as the invading people is detected and located in the interior of the alert area, the proposed system will immediately alarm the security guards by MMS of cellular networks or a customized App installed in smart phones. Besides, this work also proposes a sliding-window based alarm mechanism to practically and robustly improve the detection rate and reduce the false alarm rate of detection. The experimental results will demonstrate that the proposed system can be indeed applied in a real field and provide a satisfied performance.

关键词： Virtual Fence Gaussian Mixture Model Pedestrian Detection adaboost algorithm

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A Face Detection Method Based on Mixed Characteristics

A Face Detection Method Based on Mixed Characteristics

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2012电子信息与电气工程国际学术会议(EIEE2012)

作者： Zhang Jian 1 School of Information and Electrical Engineering,Hunan University of Science and Technology, Hu Nan Xiang Tan 411100,china Zheng Teng Jiao 2 School of Information and Electrical Engineering,Hunan University of Science and Technology, Hu Nan Xiang Tan 411100,china Li Kun 3 ,Wang Wei 3 ,Fu Xiang 3 School of Information and Electrical Engineering,Hunan University of Science and Technology, Hu Nan Xiang Tan 411100,china

Face detection methods based on mixed features and adaboost algorithm are presented. A method combining local Walsh features and global PCA features is proposed, and classifiers based on PCA features are ensemble to i... 详细信息

关键词： adaboost algorithm Walsh characteristics PCA characteristics Face Detection

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Automatic Fault Recognition for Losing of Train Bogie Center Plate Bolt

Automatic Fault Recognition for Losing of Train Bogie Center...

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2012 IEEE 14th International Conference on Communication Technology

作者： Nan Li Zhenzhong Wei Zhipeng Cao Xinguo Wei Beijing University of Aeronautics & Astronautics BUAA

ISBN: (纸本)9781467321006

This paper proposes an automatic recognition method for losing of train bogie center plate bolt (TBCPB),which initially locates the bolt region based on gray projection and spatial filter,and then acquires the accurate position of bolt region combined with its gradient feature,finally extracts the Haar-like features of bolt region and designs a classifier based on the adaboost *** of experiments demonstrate that the method compresses noise effectively and overcomes the complexity of various *** is also a robust method to images with poor quality,such as blur,poor illumination and excess *** average fault recognition accuracy is 95.9%.

关键词： automatic recognition Haar-like feature adaboost algorithm cross-validation

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An Extended Set of Haar-like Features for Bird Detection Based on adaboost

An Extended Set of Haar-like Features for Bird Detection Bas...

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International Conference on Signal Processing, Image Processing and Pattern Recognition (SIP 2011)

作者： Huang, Chih-Cheng Tsai, Chun-Yi Yang, Horng-Chang Natl Taitung Univ Dept Comp Sci & Informat Engn Taitung Taiwan

ISBN: (纸本)9783642271823

As adaboost is an efficient method to select features, we investigate its capability in selecting effective features from a set of Haar-like features for bird detection. Moreover. adaboost is also used to construct a strong classifier for the task of detecting birds from a set of weak classifiers. We propose to add specially designed new Haar-like features to increase the detection rate of interested objects, here, namely birds. Our experiment shows that this method can increase the TPR (True Positive Rate) and decrease the FPR (False Positive Rate). In addition, a motion detection algorithm is used to detect moving objects, which are segmented from background. Using the strong classifier trained from adaboost algorithm, segmented objects are classified as bird or not. The advantage of this approach is that higher performance and real-time detection can be achieved due to the fact that the strong classifier needs not to examine all the possible sub-windows of the input image. Thus, this method can further decrease the rate of false positive.

关键词： bird detection motion detection adaboost algorithm Haar-like features

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Infinite adaboost and Its Application on Fault Diagnosis for Analog Circuits

Infinite AdaBoost and Its Application on Fault Diagnosis for...

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2nd International Conference on Manufacturing Science and Engineering

作者： Wang, Hexun Liu, Chong Sun, Yuqing Dalian Maritime Univ Marine Engn Coll Dalian 116026 Peoples R China

ISBN: (纸本)9783037850398

adaboost algorithm can achieve better performance by averaging over the predictions of some weak hypotheses. To improve the power of classification ability of adaboost, an infinite ensemble learning framework based on the Support Vector Machine was formulated. The framework can output an infinite adaboost through embedding infinite hypotheses into a new kernel of Support Vector Machine. The stump kernel embodies infinite decision stumps. At last, the algorithm was used in fault diagnosis for analog circuits. Experimental results show that infinite adaboost with Support Vector Machine is superior than finite adaboost with the same base hypothesis set. The purpose of enhancing classification accuracy of adaboost algorithm is achieved.

关键词： adaboost algorithm SVM Stump Kernel Hyper-Plane Classification Accuracy

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Dependence structure of the commodity and stock markets, and relevant multi-spread strategy

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2011年第21-22期390卷 3842-3854页

作者： Kim, Min Jae Kim, Sehyun Jo, Yong Hwan Kim, Soo Yong Korea Adv Inst Sci & Technol Dept Phys Taejon South Korea

Understanding the dependence structure between the commodity and stock markets is a crucial issue in constructing a portfolio. It can also help us to discover new opportunities to implement spread trading using multiple assets classified in the two different markets. This study analyzed the dependence structure of the commodity and stock markets using the random matrix theory technique and network analysis. Our results show that the stock and commodity markets must be handled as completely separated asset classes except for the oil and gold markets, so the performance enhancement of the mean-variance portfolio is significant as expected. In light of the fact that WTI 1 month futures and four oil-related stocks are strongly correlated, they were selected as basic ingredients to complement the multi-spread convergence trading strategy using a machine learning technique called the adaboost algorithm. The performance of this strategy for non-myopic investors, who can endure short-term loss, can be enhanced significantly on a risk measurement basis. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.

关键词： Commodity Random matrix theory Network analysis Multi-spread trading adaboost algorithm

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A Surveillance System for a Farm

A Surveillance System for a Farm

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International Conference on Informatics Engineering and Information Science (ICIEIS 2011)

作者： Kim, A-Ram Rhee, Sang-Yong Seok, Seung-Joon Lee, Hong-Chang Kim, Young-Baek Kyungnanm Univ Dept Comp Engn Gyeonnganm South Korea

ISBN: (纸本)9783642254826;9783642254833

This paper proposes a smart surveillance system to be able to identify person concerned or animal in order to prevent the crops stolen. Until now most of surveillance system use a method that records images by surveillance camera or sensor network. This kind of surveillance system has limitation not to identify person or not. The limitation bothers a farm supervisor. To overcome the problem, we detect moving object using codebook and distinguish whether to human or noise by using adaboost algorithm. Also, this system transmits image information to the supervisor. But even though detected object is person, it is not easily distinguishable whether person concerned or dubious one. That is why because of low resolution of images. To make unnecessary emergency alarm not ring, we adopt smart card technology.

关键词： Surveillance system Human identification adaboost algorithm

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Detection of Movements of Head and Mouth to Provide Computer Access for Disabled

Detection of Movements of Head and Mouth to Provide Computer...

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16th Annual International Conference on Technologies and Applications of Artificial Intelligence (TAAI)

作者： Song, You Luo, Yunfeng Lin, Jun BUAA Coll Software Beijing Peoples R China Nanyang Technol Univ Sch Comp Engn Singapore Singapore

ISBN: (纸本)9780769546018

This paper analyzes the biometric identification and tracking related technologies of human-computer interaction. Based on adaboost face detection algorithm, we propose a position-based head motion detection algorithm, which does not depend on the specific biometric identification and tracking. It uses feature classification method to detect mouth's opening and closing actions. We also design a software system to operate computer by image detection of head and mouth movements. The combinations of head and mouth movements, are mapped to various mouse events, including move, click and drag, and so on. This system can be used for the upper limb disabled who failed to use the traditional mouse and keyboard. Furthermore, it can also be used for general computer users to do neck rehabilitation training, computer somatic games, etc.

关键词： adaboost algorithm Face Detection Mouse Human-Computer Interaction

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Computationally Efficient Vehicle Tracking for Detecting Accidents in Tunnels

Computationally Efficient Vehicle Tracking for Detecting Acc...

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International Conference on Multimedia, Computer Graphics and Broadcasting (MulGraB 2011)

作者： Kim, Gyuyeong Kim, Hyuntae Park, Jangsik Kim, Jaeho Yu, Yunsik Inst Busan Convergence IT Devices San 24 Pusan 614714 South Korea Dong Eui Univ Dept Multimedi Engn Busan South Korea Kyungsung Univ Dept Elect Engn Busan South Korea Pusan Natl Univ Dept Elect Engn Busan South Korea

ISBN: (纸本)9783642271854

It is becoming increasingly important to construct tunnel for transportation time and space utilization. To avoid the large scale of damages of vehicle accident in the tunnel, it is necessary to have a tunnel accidents monitoring system to minimize and discover the accidents as fast as possible. In this paper, a moving and stopped vehicle detection algorithm is proposed. It Detecting vehicle based on morphological size information of object according to distance and adaboost algorithm. Kalman filter and LUV color informations of rear lamp are used to detect stopped vehicles. Results of computer simulations show that proposed algorithm increases detection rate more than other detection algorithms.

关键词： Background estimation adaboost algorithm Kalman Filter LUV color

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A Real-Time Vision-Based Framework for Human-Robot Interaction

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2nd International Visual Informatics Conference

作者： Lam, Meng Chun Prabuwono, Anton Satria Arshad, Haslina Chan, Chee Seng Univ Kebangsaan Malaysia Fac Informat Sci & Technol Ukm Bangi 43600 Selangor De Malaysia Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur 530603 Malaysia

ISBN: (纸本)9783642251900;9783642251917

Building human-friendly robots which are able to interact and cooperate with humans has been an active research field in recent years. A major challenge in this field is to develop robots that can interact and cooperate with humans by understanding human communication modalities. Nonetheless, human face is a dynamic object and has a high degree of variability in its appearance, which makes face detection a difficult problem. In this paper, we present a real-time vision-based framework to detect human face and analysis of the human face direction in window area to interact with robot. A cascade of feature detectors trained with boosting technique has been employed. Experimental results using servo motors connect to SD21 and PIC16F887A microcontroller: and the MIABOT Pro have validated our approach. Our future work is to build an intelligent wheelchair whose motion can be controlled by the user's face direction.

关键词： Vision-based framework human-robot interaction face detection adaboost algorithm Visual Informatics

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