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检索条件"主题词=Adaboost algorithm"

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Multi-View Face Detection Based on Improved adaboost algorithm

Multi-View Face Detection Based on Improved Adaboost Algorit...

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2018 2nd International Conference on Computer Science and Intelligent Communication(CSIC 2018)

作者： Han Zishuo Wang Chunping Shijiazhuang Campus Army Engineering University

Aiming at the problem of the traditional adaboost algorithm with fast detection but low accuracy in multi-view face detection, a modified adaboost algorithm for face detection was proposed in this ***,in order to excluding the interference of most non-face regions, the whole image area is detected with skin color segmentation algorithm,then we use cascade structure classifier trained by adaboost algorithm which addes the extended Haar features to classify the human face candidate regions, thereby the human face can be posited. Experimental results show that the algorithm of this paper can not only effectively improve the human face detection rate and detection speed, but also reduce the false detection rate of multi-view face, in short, the algorithm has a good practical value.

关键词： Face Detection adaboost algorithm Skin Color Detection

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Face detection system based on adaboost algorithm

Face detection system based on adaboost algorithm

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2014 International Conference on Computational Intelligence and Industrial Engineering(CIIE 2014)

作者： Yingjie Chen Xiao Huang Department of Electronic and Engineering Beijing University of Civil Engineering and Architecture

This paper aims to detect people's face by using haar feature and adaboost algorithm with Open CV,which can realize the face detection from static or dynamic images. We configured vc++2010 and Opencv2.1 and performed an experiment on this experiment platform. In this paper shape information and motion information were combined in the detection process,compared with the previous face detection method,the combination of the shape information and motion information can make the model of target more compact. This face detection system can detect both front face and profile face,two classifiers were used independently at the same time,which made it more comprehensive. The experiment results show that this face detection system has good detection effect in processing the images from the recorded video,or real-time images captured by a USB camera. In order to meet the detection of people of different postures,and different light conditions,we consider specially when training the classifier. Experiment results show that the performance of the proposed method is higher than the basic adaboost in the sense of detecting fewer nonfaces. The testing effect is good,at the same time meet the real-time requirements,thus the studying of face detection in the real situations in this paper has a strong practical significance.

关键词： adaboost algorithm haar feature face detection

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Designing and Optimizing the Method for Pedestrian Detection Based on adaboost algorithm

Designing and Optimizing the Method for Pedestrian Detection...

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The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

作者： Yunpeng Su Binwen Fan Qiliang Yang Key Laboratory of IOT Terminal Pivotal Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen China

ISBN: (纸本)9781479951499

The designing based on adaboost algorithm not only achieved the nighttime pedestrian detection module of auxiliary driving system,but also realized the system optimization on issues of low detection speed and *** this design,variable step length and partition scanning track methods are used to improve the detection speed and variance normalization approach was applied to eliminate the influences to the detection result caused by light factors,moreover,multi-scale fusion technology was utilized to make analysis to the detected rectangular box,in this case,the redundant portion of detection result can be removed,and thus improved the detection rate and reduced the false alarm rate.

关键词： Pedestrian Detection adaboost algorithm multi-scale fusion

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Using adaboost algorithm Along with Artificial Neural Networks for Efficient Human Emotion Recognition From Speech

Using Adaboost Algorithm Along with Artificial Neural Networ...

引用

International Conference on Control, Automation, Robotics and Embedded Systems

作者： Jasdeep Singh Bhalla Anmol Aggarwal Department of Computer Science Bharati Vidyapeeth's College of Engineering Department of Information Technology Bharati Vidyapeeth's College of Engineering

ISBN: (纸本)9781467361521

Emotion Recognition from speech has evolved itself as the most significant research area in the field of affective computing. In this paper, two emotional speech datasets, have been analyzed, based on gender distinction (male and female speech). This paper introduces a new approach of speech-emotion recognition based on the use of adaboost classification algorithm. Artificial neural network has been implemented for pattern classification and recognition. English is used as the basic language for the testing of the method. We have recognized the emotions into four different groups happy, normal, sad and anger by using adaboost algorithm and ANN. The output for the two datasets are evaluated and analyzed.

关键词： Speech Recognition adaboost algorithm Artificial Neural Networks Emotion Recognition adaboost Classification

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FACE DETECTION BASED ON IMPROVED adaboost algorithm IN E-LEARNING

FACE DETECTION BASED ON IMPROVED ADABOOST ALGORITHM IN E-LEA...

引用

2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems

作者： Wansen Wang Huifang Niu Capital Normal University

This paper is based on the background of learners' expression recognition in emotion recognition interactive E-Learning. This paper aims at time-consuming of training samples and weights degradation two problems of traditional adaboost algorithm, proposes a decile eigenvalue adaboost algorithm and joins FPR (False Positive Rate) in this algorithm. The experiments use improved adaboost algorithm in E-Learning face detection achieved good effect, and the results provide good conditions for the follow-up E-Learning expression feature extraction.

关键词： E-Learning Face detection FPR eigenvalue adaboost algorithm

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Studies on Face Detection Based on Improved adaboost algorithm

Studies on Face Detection Based on Improved AdaBoost Algorit...

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2011 International Conference on Intelligent Computing and Integrated Systems(ICISS 2011)

作者： Wang Jiang-Bo School of Computer Science and Engineering Guilin University of Electronic Technology Guilin, China Li Shao-Wen Network Center Guilin University of Electronic Technology Guilin, China

This paper proposes a method based on improved adaboost algorithm to detect face. This method improves the training algorithm of strong classifier by abolishing the redundant feature and optimizing the selection of weak classifier. Besides, the method also optimizes the cascade classifier. The experimental results show that this algorithm achieves face detection well with less computing, higher accuracy and real-time.

关键词： face detection adaboost algorithm Haar-like characteristic

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The Application of the adaboost algorithm in the Text Classification

The Application of the AdaBoost Algorithm in the Text Classi...

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IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference

作者： TU Chengsheng XU Bing LIU Huacheng Computer Science and Engineering College Chongqing Three Gorges University Wanzhou Chongqing China Sichuan Vocational and Technical College Chengdu Sichuan China

Boosting is a representative combined predictive method for improving learning accuracy in machine learning. adaboost algorithm is the most typical one in the Boosting family. This paper briefly introduced the adaboost algorithm, analyzed and discussed the application of *** and *** algorithm as solving the single label problem, and finally discussed and analyzed the adaboost.R algorithm to solve a regression problem.

关键词： Machine learning Combined prediction adaboost algorithm Text classification

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A New Approach to Face Detection based on YCgCr Color Model and Improved adaboost algorithm

A New Approach to Face Detection based on YCgCr Color Model ...

引用

International Conference on Communication and Signal Processing

作者： Rosali Mohanty M. V. Raghunadh Electronics and Communication Engineering Department NIT Warangal India

ISBN: (纸本)9781467385497

Human face detection plays considerably important role in various biometric applications like crowd surveillance, photography, human-computer interaction, tracking, automatic target recognition, artificial intelligence and various security applications. Varying illumination conditions, color variance, brightness, pose variations are major challenging problems for facial detection. Skin color based segmentation and adaboost based facial detection scheme are the two most widely used techniques for face detection. But skin color segmentation method has very high false positive detection rate in images with complicated background and adaboost algorithm does not provide desired results for detecting images having multiple pose and multiple faces. Apart from this, adaboost approach has higher accuracy, but slower speed and skin color segmentation method has a faster speed of detection, but lower accuracy;and. So our paper proposes a novel facial detection scheme based on the integration of YCgCr based skin color segmentation and improved adaboost algorithm. Also morphological operators are applied to improve the detection performance. From the experimental results, it can be deduced that the proposed face detection algorithm improves the detection speed, accuracy and capable of real time face detection. Simulation results are used to show that our proposed method achieves accuracy of approximately 97% and has considerably good performance on images having complex background and can detect faces of various sizes, postures and expressions, under uncontrolled lighting environments.

关键词： Face detection Skin color segmentation YCgCr color model adaboost algorithm

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Miner Face Detection is Based on Improved adaboost algorithm

Miner Face Detection is Based on Improved AdaBoost Algorithm

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International Conference on Computer Science and Network Technology

作者： Chao JIANG Gu-yong HAN Lei TIAN Song LU Wei-xing HUANG Air Force Service College

ISBN: (纸本)9781467329637

This article connects with Coal mine video monitoring image be impacted for special environment, which be vulnerable to mineral dust in coal mines, light, as well as miner's safety helmet for the realization of face detection in real-time and accuracy, I will study on face identification and analysis on the characters of behavior in the follow-up work for getting a good foundation, which will be in intelligent Coal mine video monitoring. This article simulates rectangle Haar-like character and Extended Haar-like character of the adaboost algorithm about face detection in real-time and accuracy, is based on OpenCV, also describes briefly the rectangular Haar-like characteristic model and about computational algorithm and faster algorithm of the characteristic value, analysis detailedly extended Haar-like character model and the characteristic value of computational algorithm-integral image. Experimental resulted show that extended Haar-like characteristic model can be implemented more quickly and more accurately in the miners' face detection, as well as real-time.

关键词： adaboost algorithm Face detection Machine vision Monitoring image Facial Recognition robot vision Miners Coal mines video monitoring Character value engineering

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An adaboost algorithm with SVM Based on Nonlinear Decision Function

An AdaBoost Algorithm with SVM Based on Nonlinear Decision F...

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2009 International Conference on Computational Intelligence and Natural Computing(CINC 2009)

作者： Wei Wu , Zhang Yanan School of Automation Science and Engineering South China University of Technology Guangzhou,China 510640 Wu Linlin School of Energy & Power Engineering Xi’an Jiaotong University Xi’an , China 710049

This paper presents a method of using nonlinear decision function to improve the performance of adaboost with SVM based weak learners. Compared with the existing adaboostSVM methods,this method ,named ERBF-adaboostSVM ,has advantages of higher hate rate and better generalization performance. This method also provides non-linear separator in the weak learner space and classifies accurately more examples. Experimental results demonstrated that ERBF-adaboostSVM achieve better generalization performance and higher hate rate than the existing SVM and adaboostSVM methods.

关键词： adaboost algorithm SVM nonlinear decision function

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