Measuring social signals has often proved challenging as they are often characterized by subtle movements which are difficult to detect. Head pose is one such social signal used to indicate where an individual's a...
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ISBN:
(纸本)9781538692769
Measuring social signals has often proved challenging as they are often characterized by subtle movements which are difficult to detect. Head pose is one such social signal used to indicate where an individual's attention is focused. This paper will discuss the problem of head pose estimation by defining the problem in terms of two fields of view, pan and tilt. A novel approach for head pose estimation is described that uses histogram of oriented gradients with support vector machines. The approach is compared with a template matching approach, among others, using a well-known dataset. The results show that the histogram of oriented gradients approach is able to determine head pan to within one class approximately 72% of the time, and head tilt to within one class approximately 71% of the time.
Hopfield neural network is utilized to enhance x-ray image of thick steel pipe welding, and a gray mapping matrix is constructed to replace traditional gray transformation curves and functions in this paper. The maxim...
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ISBN:
(纸本)9780769538655
Hopfield neural network is utilized to enhance x-ray image of thick steel pipe welding, and a gray mapping matrix is constructed to replace traditional gray transformation curves and functions in this paper. The maximum dimension of the gray mapping matrix is 256(X)256, so the calculation time has little relation with the size of the image. The criterion function of image quality is used to evaluate the quality of the transformed image. In proposed approach, the problem of image enhancement is transformed to an optimization problem, so the normalization of gray values for each pixel is not necessary. The energy function that improves the performance of image enhancement is also given for Hopfield neural network.
The co-occurrence matrix, a two-dimensional histogram of pairs of sample amplitudes, is explored as a representation of the digital speech waveform. Co-occurrence matrix representations support a hypothesis-testing ap...
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The co-occurrence matrix, a two-dimensional histogram of pairs of sample amplitudes, is explored as a representation of the digital speech waveform. Co-occurrence matrix representations support a hypothesis-testing approach to digital speech analysis. This approach is pursued in the formulation of a quantitative (chi-square) measure of sample amplitude dependence, based on co-occurrence matrices. This measure, which is higly sensitive to quasi-periodicity, is shown to lead to a good estimator of the pitch period of voiced speech. Co-occurrence matrix representations are employed in conjunction with pattern classification methods in experiments involving the voiced-unvoiced-silence analysis of speech, and in an experimental pitch extraction algorithm which is tested on continuous speech.
The importance of proper hygienical behaivour is essential in today's word especially during an ongoing pandemic. Wearing mask became mandatory in many countries during the COVID-19 Pandemic. Recognizing whether p...
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ISBN:
(纸本)9781728195438
The importance of proper hygienical behaivour is essential in today's word especially during an ongoing pandemic. Wearing mask became mandatory in many countries during the COVID-19 Pandemic. Recognizing whether people are wearing masks is complicated image recognition task which could be facilitated and automated with machine learning techniques. Camera streams are widely available in indoor environments which can be used for object detection and imageprocessing. Convolutional Neural Networks have been successfully applied in image classification and object recognition task in various application areas. There are already trained and openly available general purpose convolutional neural networks which can be used as an initial version for specific applications. A number of different image datasets are also available for research and industrial purposes. The InceptionV3 Neural Network architecture was used to tailored to determine whether a mask is being worn or not using transfer learning techniques, and convolutional neural networks. A variational autoencoder has also been trained to normalize the dataset with respect to skin colour, angle of the head and among other parameters. This paper describes the implementation of a mask recognition software using transfer learning, a convolutional neural network and a variational autoencoder.
Super-Resolution (SR) processing is a technique that produces a High - Resolution (HR) image from a range of Low - Resolution (LR) images. There are many methods for implementing the SR signalprocessing. In this pape...
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ISBN:
(纸本)9781467356046
Super-Resolution (SR) processing is a technique that produces a High - Resolution (HR) image from a range of Low - Resolution (LR) images. There are many methods for implementing the SR signalprocessing. In this paper, we introduce a specific transformation that were developed in the recent years called Curvelet Transform (CT), and then apply it in SR processing to obtain a quality improvement of SR images. We discuss two separate algorithms using the Discrete Curvelet Transform (DCT) and then compare them based on the results of HR images. We find out that the first algorithm, named the iterative algorithm can produce better HR images than the second one, the Interpolation algorithm. However, the iterative algorithm also take more computational cost than that of the Interpolation Algorithm. It is a reasonable trade-off between images quality and processing speed. We also made a comparison between our algorithms and previous works such as the Projection onto Convex Sets (POCS) and the Nearest Neighbourhood algorithms to show the quality improvement.
This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity w...
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ISBN:
(纸本)9781479961207
This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity with block coding prevents the performance degradation induced by signal multiplexing. However, the computational complexity of a joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes the use of a repetition code in the overloaded MIMO-OFDM system. In addition, QR decomposition with M-algorithm (QRM) maximum likelihood decoding (MLD) is applied to the decoding of the repetition code. QRM-MLD significantly reduces the amount of joint decoding complexity. In addition, virtual antennas are employed in order to increase the throughput that is reduced by the repetition code. It is shown that the proposed scheme reduces the complexity by about 1/48 for 6 signal streams with QPSK modulation while the BER degradation is less than 0.1dB at the BER of 10(-3).
This paper explores control parameter tuning for the Eulerian Video Magnification (EVM) process using a pair comparison-based interactive differential evolution (PCB-IDE) algorithm. Interactive evolutionary optimizers...
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ISBN:
(纸本)9781538692769
This paper explores control parameter tuning for the Eulerian Video Magnification (EVM) process using a pair comparison-based interactive differential evolution (PCB-IDE) algorithm. Interactive evolutionary optimizers have a history of being applied to video/image post-processing tasks because assessing the quality of video data is objectively difficult without subjective assessment by users. The EVM technique magnifies motion and color variations within a video in a manner similar to a visual microscope. Applying EVM to video sequences allows the observation of known physical phenomenon by using only video data, which is critical to development of camera based monitoring applications. The proposed PCB IDE assists experts in determining the optimal parameters for EVM process to better identify visual changes and correlate them to physical phenomenons.
Real-time monitoring of the laser-based applications is becoming a main issue for quality analysis in the steel manufacturing industry. The paper suggests a solution achieving an automated real-time quality inspection...
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ISBN:
(纸本)0780377834
Real-time monitoring of the laser-based applications is becoming a main issue for quality analysis in the steel manufacturing industry. The paper suggests a solution achieving an automated real-time quality inspection in laser welding applications. A composite system composed of soft-computing and traditional techniques has been considered for its positive impact on the reduced computational once compared with more traditional approaches.
The aim of this work is to analyze the applicability of machine learning methods to the problems of diagnosing on the cardiovascular system data and develop a novel technique for automating this process to support dec...
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ISBN:
(纸本)9781538685273
The aim of this work is to analyze the applicability of machine learning methods to the problems of diagnosing on the cardiovascular system data and develop a novel technique for automating this process to support decision making in cardiology. Here, the results obtained with the help of classifiers based on random decision forests are examined, and a proprietary numerical experiment is performed with the Doppler flowmetry data. Considerable attention is paid to data processing and reduction of the input vector dimension for analysis.
This paper introduces the composition of the autocollimator tracking system, and analyses in detail the imageprocessing part and servo tracking part of the system. The imageprocessing part uses TMS320DM642 DSP to co...
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ISBN:
(纸本)9781467317443
This paper introduces the composition of the autocollimator tracking system, and analyses in detail the imageprocessing part and servo tracking part of the system. The imageprocessing part uses TMS320DM642 DSP to complete the image acquisition and image display. Using RS232 serial ports to transmit each frame offset of target to the servo tracking part. According to the offset information, the servo tracking part makes use of TMS320F2812 DSP to complete real-time tracking. Autocollimator tracking system uses two rhombic prisms to ensure real-time transmission of optical path. Experiments show that the autocollimator tracking system can achieve 1HZ real-time tracking and fully meets the project needs.
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