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 ...
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ISBN:
(纸本)9780769536453
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 nonlinear 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.
In order to improve the accuracy of face detection, this paper proposes a method based on combination of skin color model and improved adaboost algorithm. Using skin color model with YCbCr color space to detect the sk...
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ISBN:
(纸本)9781728136608
In order to improve the accuracy of face detection, this paper proposes a method based on combination of skin color model and improved adaboost algorithm. Using skin color model with YCbCr color space to detect the skin color, obtain the area to be detected, and then we can locate accurately the face position with the adaboost face detection algorithm. Because the traditional adaboost face detection algorithm needs a long time training and can not effectively distinguish feature values which are aggregated distribution, we have improved adaboost algorithm based on two-threshold and a new method about suppression of weights updating which which prevents excessive weight gain and avoids the phenomenon of degradation during training in adaboost.
The adaboost algorithm enables weak classifiers to enhance their performance by establishing the set of multiple classifiers, and since it automatically adapts to the error rate of the basic algorithm ill training thr...
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ISBN:
(纸本)9783642181283
The adaboost algorithm enables weak classifiers to enhance their performance by establishing the set of multiple classifiers, and since it automatically adapts to the error rate of the basic algorithm ill training through dynamic regulation of the weight of each sample, a wide range of concern has been aroused. This paper primarily makes some relevant introduction of adaboost, and conducts an analysis and research of several aspects of the algorithm itself.
The use of fires represents one of the principal methods to convert tropical forest ecosystems into other land-uses. To better target forest fire management and regulation policies, a better understanding of the areas...
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ISBN:
(纸本)9781538654903
The use of fires represents one of the principal methods to convert tropical forest ecosystems into other land-uses. To better target forest fire management and regulation policies, a better understanding of the areas prone to forest fires is needed. This study focuses on forest fires in the Peruvian Amazon and tropical Andes regions. First, the areas where forest fires are most prevalent are identified using Kernel Density Analysis. Second, the risk on fire within two forest fire hotspot locations is assessed using the adaboost algorithm. The results of this study show that forest fire is most extensive in the departments of Ucayali/Huanuco and San Martin. Furthermore, forest fire risk maps show that most of the highly to very highly susceptible areas in Ucayali/Huanuco are clustered within a single region, while in San Martin, susceptible areas are more widely scattered throughout the department. The fire risk maps generated in this study could contribute to forest fire management and research efforts in the Peruvian Amazon and tropical Andes regions.
This paper proposes an automatic and robust method to detect human faces from background that is capable of processing frames of video sequence rapidly while achieving high detection rates regardless of scale, rotatio...
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ISBN:
(纸本)9781509007684
This paper proposes an automatic and robust method to detect human faces from background that is capable of processing frames of video sequence rapidly while achieving high detection rates regardless of scale, rotation and shelter. The field of this work is the incorporation of adaboost and self-adaption region of interest to reducing time complexity in testing time. Next template matching is aim to alleviate common problems in conventional face detection using adaboost method such as: inconsistent performance due to sensitivity to rotation of head pose and the obscured of other object. In the final step, focusing on the phenomena of overmatching in test time, this paper proposes an error-correction-factor to overcome.
Face detection is a fundamental and important research theme in the topic of Pattern Recognition and Computer Vision. Now, remarkable fruits have been achieved. Among these methods, statistics based methods hold a dom...
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ISBN:
(纸本)9781510600546
Face detection is a fundamental and important research theme in the topic of Pattern Recognition and Computer Vision. Now, remarkable fruits have been achieved. Among these methods, statistics based methods hold a dominant position. In this paper, adaboost algorithm based on Haar-like features is used to detect faces in complex background. The method combining YCbCr skin model detection and adaboost is researched, the skin detection method is used to validate the detection results obtained by adaboost algorithm. It overcomes false detection problem by adaboost. Experimental results show that nearly all non-face areas are removed, and improve the detection rate.
This paper proposes a face detection algorithm of combining skin color segmentation and adaboost *** algorithm set up the skin Gaussian model in YCbCr color space using skin color clustering *** sort out the region of...
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ISBN:
(纸本)9781509046584
This paper proposes a face detection algorithm of combining skin color segmentation and adaboost *** algorithm set up the skin Gaussian model in YCbCr color space using skin color clustering *** sort out the region of skin color,use adaboost algorithm to train a classifier to detect face in the *** on our experiments,the proposed method shows good results with significant improvements of low error detection rate and better detection speed in both simple and complex background.
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 distincti...
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ISBN:
(纸本)9781467361538
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.
In view of the higher mistaken-detection rate problem of the human face detection in complex conditions, we put forward an improved algorithm. This article Proposes one kind of the method Which unifies the level of di...
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ISBN:
(纸本)9783038353140
In view of the higher mistaken-detection rate problem of the human face detection in complex conditions, we put forward an improved algorithm. This article Proposes one kind of the method Which unifies the level of difference between the threshold and the feature value of the weak classifier with the weak classifier's overall error rate. Compared to the method which only based on the overall classification error rate to update the weights, this method can achieve higher detection rate while reduces the mistaken-detection rate. This article redefines the training error which is caused When we train the weak classifier, and Proposes MCE-adaboost algorithm. The new definition of training error will pay more attention to the error Which erroneously estimates the face Sample as non-face sample;this much more conforms to face detection of this special target detection issue. The experimental results show that MCE-adaboost algorithm can effectively improve the detection Performance of the final classifier.
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 o...
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ISBN:
(纸本)9781467318556;9781467318570
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.
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