In this paper, we propose a novel feature type to recognize human actions from video data. By combining the benefit of Volume Local Binary patterns and Optical Flow, a simple and efficient descriptor is constructed. M...
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In the literature of face recognition many algorithms have been proposed which extract local texture features for robust face recognition. But for final computation of the feature the information about central pixel i...
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ISBN:
(纸本)9781479970025
In the literature of face recognition many algorithms have been proposed which extract local texture features for robust face recognition. But for final computation of the feature the information about central pixel is not taken into account. In this paper, we propose a novel method which utilizes Local Ternary pattern and Booth's Algorithm techniques to capture the local face features, which utilizes central pixel for computation of the feature. Face images are partitioned into small windows and classification works better with local descriptors, a Non- overlapping block wise processing is done on image to limit the features. The Support Vector Machine (SVM) and KNN classifier with proposed similarity measure is used for face recognition. Finally, ROC and CMC are plotted for analysis of the system. Experiments are conducted on ORL and faces94 datasets demonstrates that the proposed method has better classification accuracy than previously proposed methods.
The proceedings contain 27 papers. The special focus in this conference is on Artificial Neural Networks for patternrecognition. The topics include: Large margin distribution learning;a decorrelation approach for pru...
ISBN:
(纸本)9783319116556
The proceedings contain 27 papers. The special focus in this conference is on Artificial Neural Networks for patternrecognition. The topics include: Large margin distribution learning;a decorrelation approach for pruning of multilayer perceptron networks;unsupervised active learning of CRF model for cross-lingual named entity recognition;incremental feature selection by block addition and block deletion using least squares SVRs;low-dimensional data representation in data analysis;analyzing dynamic ensemble selection techniques using dissimilarity analysis;hidden Markov models based on generalized Dirichlet mixtures for proportional data modeling;majority-class aware support vector domain oversampling for imbalanced classification problems;forward and backward forecasting ensembles for the estimation of time series missing data;dynamic weighted fusion of adaptive classifier ensembles based on changing data streams;combining bipartite graph matching and beam search for graph edit distance approximation;computing upper and lower bounds of graph edit distance in cubic time;a new multi-class fuzzy support vector machine algorithm;a reinforcement learning algorithm to train a Tetris playing agent;automatic bridge crack detection - a texture analysis-based approach;part-based high accuracy recognition of serial numbers in bank notes;comparative study of feature selection for white blood cell differential counts in low resolution images;end-shape recognition for Arabic handwritten text segmentation;intelligent ensemble systems for modeling NASDAQ microstructure;face recognition based on discriminative dictionary with multilevel feature fusion;investigating of preprocessing techniques and novel features in recognition of handwritten Arabic characters and a time series classification approach for motion analysis using ensembles in ubiquitous healthcare systems.
We present a pattern-based approach for the rhythm classification task that combines an Auto-correlation function (ACF) and Discrete Fourier transform (DFT). Rhythm hypotheses are first extracted from symbolic input d...
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This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the ...
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ISBN:
(纸本)9781479935840
This paper identifies and analyses the factors that contribute to the similarity between two sets of minutiae points as well as the probability that two sets of minutiae points were extracted from fingerprints of the same finger. Minutiae-based fingerprint matching has been studied extensively in the literature, however, there is still a need for major improvement especially when it comes to comparing partial fingerprints. This paper looks at existing similarity measures;discusses their performance at discriminating between minutiae points from fingerprints of the same finger and of different fingers. The matching problem has been broken down into smaller subproblems which are easier to define and solve. Each of the scores discussed are analyzed and tested to see if they are able to deal with each of the matching subproblems. Results show that most scores in the literature fall in one of two ends of matching;good at discriminating impostor matches, or good at discriminating genuine matches. The authors propose a score which bridges these two types of scores and enables optimal impostor and genuine comparisons.
Prior information has been effectively exploited mainly using probabilistic models. In this paper, by focusing on the bias embedded in the classifier, we propose a novel method to discriminatively learn the prior bias...
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In daily conversation, people use spatial prepositions to denote spatial relationships and describe relative positions. Various quantitative relative position descriptors can be found in the literature. However, they ...
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In this paper, we improved the method of minimum squared error for robust classification by altering its classification rule. The minimum squared error method, is one of the methods to minimize the sum of the squared ...
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ISBN:
(纸本)9781479947195
In this paper, we improved the method of minimum squared error for robust classification by altering its classification rule. The minimum squared error method, is one of the methods to minimize the sum of the squared error between the output of the linear function and the desired output, which first obtains the mapping that can best transform the training sample into its class label and then exploits the obtained mapping to predict the class label of the test sample. However, the improved method classifies all the test examples by comparing the difference of predicted class labels of test examples and training examples. Through experiment in section 4, we draw a conclusion that the improved MSE (IMSE) method can reduce the classification error and get a better classification result.
Character patternrecognition is widely used in the information technology field. This paper proposes a method of character patternrecognition based on rough set theory. By giving the characters' two dimensional ...
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ISBN:
(纸本)9783038350118
Character patternrecognition is widely used in the information technology field. This paper proposes a method of character patternrecognition based on rough set theory. By giving the characters' two dimensional image, defining the location of the characteristic and abstracting the characteristic value, the knowledge table and table reduction can be ascertained. Then the decision rules can be deduced. Through the simulation of 26 English alphabets, the results illustrate this method's validity and correctness.
Ambiguous patternrecognition is a very important technology in the field of science including engineering application nowadays, it uses methods of fuzzy mathematics enabling the computer to recognize and judge the ob...
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ISBN:
(纸本)9783038351559
Ambiguous patternrecognition is a very important technology in the field of science including engineering application nowadays, it uses methods of fuzzy mathematics enabling the computer to recognize and judge the objective things. But, the research on ambiguous patternrecognition system rarely involves the field of security, while in fact both the participant of the patternrecognition and the database need to protect their privacy. This paper mainly introduces the secure multi-party computation into the field of ambiguous patternrecognition, raises a new solution for the secure multi factor ambiguous patternrecognition system under the half honest model, and proves the validity and security of the protocol.
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