this paper presents some initial results from an analysis of performance of a voice command interpretation and authorisation system using voiceprint to identify the human-commander. Two approaches based on human voice...
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this paper presents some initial results from an analysis of performance of a voice command interpretation and authorisation system using voiceprint to identify the human-commander. Two approaches based on human voice related algorithms are proposed. Mel-frequency cepstral coefficient (MFCC) and perceptual linear predictive (PLP) are two feature extraction methodsthat are closely mimic the human auditory system. the two methods were applied to the proposed system to determine their suitability for use in a commander recognition system. Vector Quantization (VQ) with Linde-Buzo-Gray (LBG) iterative algorithm was used for clustering for the classification of commanders. the performance of the algorithms was evaluated to compare between two methods in MATLAB simulation environment based on, false rejection rate (rejecting an authorised commander), false acceptance rate (accepting unauthorised commander) and the execution time. Based on the initial results, bothmethods achieved accurate classification and PLP method has shown better execution time and lower false-acceptance rate compared to the MFCC. the combined approach (MFCC-PLP) did not show considerable improved performances to the individual feature models PLP and MFCC without incurring high computational costs that will compromise the performance of the speaker recognition tasks. therefore, PLP method is the best candidate for command-recognition system to be developed in the second phase of this research.
Reactive rhythm bands to imagined speeds of index finger movement and offline classification of imagined speeds were explored in the paper. EEG was recorded when 4 subjects executed motor imagery of two tasks at first...
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Grasping by Components (GBC) is a very important component of any scalable and holistic grasping system that abstracts point cloud object data to work with arbitrary shapes with no apriori data. Superquadric represent...
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Grasping by Components (GBC) is a very important component of any scalable and holistic grasping system that abstracts point cloud object data to work with arbitrary shapes with no apriori data. Superquadric representation of point cloud data is a suitable parametric method for representing and manipulating point cloud data. Most Superquadrics based grasp hypotheses generation methods perform the step of classifying the parametric shapes into one of different simple shapes with apriori established grasp hypotheses. Such a method is suitable for simple scenarios. But for a holistic and scalable grasping system, direct grasp hypothesis generation from Superquadric representation is crucial. In this paper, we present an algorithm to directly estimate grasp points and approach vectors from Superquadric parameters. We also present results for a number of complex Superquadric shapes and show that the results are in line with grasp hypotheses conventionally generated by humans.
Reactive rhythm bands to imagined speeds of index finger movement and offline classification of imagined speeds were explored in the paper. EEG was recorded when 4 subjects executed motor imagery of two tasks at first...
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Reactive rhythm bands to imagined speeds of index finger movement and offline classification of imagined speeds were explored in the paper. EEG was recorded when 4 subjects executed motor imagery of two tasks at first-person perspective that involved left index fingers at two speeds (4Hz and 1Hz, trained and paced by metronome). Relatively prominent rhythmic activities around 10-13 Hz and 24~26 Hz over C3, 12~13 Hz over Cz, and 11~13 Hz, 8~10Hz, and 25~26 Hz over C4 were found by spectrum analysis. the most significant band 9-13Hz was used to construct the feature space. the Fisher discriminant analysis method (FDA), multi-layer perceptron neural network (MLP), and distinction sensitive learning vector quantization (DSLVQ) were applied in offline identification of imagined speeds respectively. the best average misclassification rates between fast and slow movement imagination by only three derivations C3, Cz, and C4 with FDA, MLP, and DSLVQ were 27.5±1%, 31.2±3.7%, and 34.6% at 3260 ms respectively. the results showed that FDA in this study was better than MLP and DSLVQ. this study demonstrated that discrimination for imagined speeds of finger movement was possible and feasible. Classification of imagined movement speeds with high accuracy based on EEG is also possible through improving methods in the paper. the study may provide a strategy to realize fine control of robots by brain-controlled robot interface.
this paper is focused on the extending Takagi-Sugeno-Kang (TSK) types fuzzy models. the propositions of the models with a fuzzy set-valued function in the consequence part as well as the models withthe fuzzy time ser...
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ISBN:
(纸本)9781424478279
this paper is focused on the extending Takagi-Sugeno-Kang (TSK) types fuzzy models. the propositions of the models with a fuzzy set-valued function in the consequence part as well as the models withthe fuzzy time series in the consequence part are presented. Also chosen theoretical aspects of the creating knowledge bases and the fuzzy reasoning procedure are presented.
Shape optimization problem for semilinear elliptic equation is considered. there is an optimal solution which is computed by the Levelset method. To this end the shape derivative of the functional is evaluated. In ord...
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ISBN:
(纸本)9781424478279
Shape optimization problem for semilinear elliptic equation is considered. there is an optimal solution which is computed by the Levelset method. To this end the shape derivative of the functional is evaluated. In order to predict the topology changes the topological derivative is employed. Numerical results confirm that the proposed framework for numerical solution of shape optimization problems is efficient.
the use of an Electrical narrow tilting car instead of a large gasoline car should dramatically decrease traffic congestion, pollution and parking problem. the aim of this paper is to give a unique presentation of the...
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ISBN:
(纸本)9781424478279
the use of an Electrical narrow tilting car instead of a large gasoline car should dramatically decrease traffic congestion, pollution and parking problem. the aim of this paper is to give a unique presentation of the geometric modeling issue of a new narrow tilting car. the modeling is based on the modified Denavit Hartenberg geometric description, which is commonly used in robotics. Also, we describe the special Kinematic of the vehicle and give a method to analyze the tilting mechanism of it. Primarily experimental results on the validation of the geometrical model of a real tilting car are given.
In this paper a comparative analysis is represented on various navigation guidance methods used for intercepting fast maneuvering moving objects. A glancing revision is introduced on relevant works within the introduc...
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ISBN:
(纸本)9781424478279
In this paper a comparative analysis is represented on various navigation guidance methods used for intercepting fast maneuvering moving objects. A glancing revision is introduced on relevant works within the introduction section. Four common methods for navigation under investigation. Results demonstrate their infirmity on smoothly intercepting a moving object. Hence, to improve the navigation guidance methods and to adapt them with robotic problems a modified version of AIPNG is proposed for 2D problems and is developed for 3D problems utilization.
According to the level of information provided in images, segmentation techniques can be categorized into two groups. One is region-labeling, which obeys the intensity-based classification methods. Although modeling t...
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ISBN:
(纸本)9781424478132
According to the level of information provided in images, segmentation techniques can be categorized into two groups. One is region-labeling, which obeys the intensity-based classification methods. Although modeling the tissue intensity is straightforward by applying local statistical methods and spatial dependencies, the results might suffer from noise and incomplete data. the second group of techniques applies active contour models, in which the objective is to find the optimal partition of the image domain using a closed or open curve by using prior constraints on the shape variation. However, estimating optimal curve is intractable due to the incomplete observation data. this paper extends a previously reported joint active contour model for medical image segmentation in a new Expectation-Maximization (EM) framework, wherein the evolution curve is constrained not only by a shape-based statistical model but also by applying a hidden variable model from the image observation. In this approach, the hidden variable model is defined by the local voxel labeling computed from its likelihood function, depended on the image functions and the prior anatomical knowledge. Comparative results on segmenting putamen and caudate shapes in MR brain images confirmed both robustness and accuracy of the proposed curve evolution algorithm.
Many age estimation methods have been proposed for various applications such as Age Specific Human Computer Interaction (ASHCI) system, age simulation system and so on. Because the performance of the age estimation is...
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ISBN:
(纸本)9781424478132
Many age estimation methods have been proposed for various applications such as Age Specific Human Computer Interaction (ASHCI) system, age simulation system and so on. Because the performance of the age estimation is greatly affected by the aging feature, the aging feature extraction from facial images is very important. the aging features used in previous works can be divided into global and local features. As global features, Active Appearance models (AAM) was mainly used for age estimation in previous works. However, AAM is not enough to represent local features such as wrinkle and skin. therefore, the research about local features is required. In previous works, local features were generally used to determine age group rather than detailed age, and the comparative studies about various local features extraction methods were not conducted. In this paper, the performances of sobel filter, difference image between original and smoothed image, ideal high pass filter (IHPF), gaussian high pass filter (GHPF), Haar and Daubechies discrete wavelet transform (DWT) are compared for extracting local features and detailed age estimation is performed by Support Vector Regression (SVR) on BERC and PAL aging database. the experimental results show that local features can be used for detailed age estimation and GHPF gives a better performance than other methods.
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