作者：
B. AbidiS. HuqM. AbidiImaging
Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville TN USA
This paper summarizes the various components of face recognition research conducted at the IRIS Lab. First, fusion of visual and thermal infrared (IR) images for robust face recognition is discussed. Two techniques ar...
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This paper summarizes the various components of face recognition research conducted at the IRIS Lab. First, fusion of visual and thermal infrared (IR) images for robust face recognition is discussed. Two techniques are implemented: data fusion and decision fusion. With the knowledge that eyeglasses block the emission of thermal energy, an algorithm is designed to detect and replace eyeglasses with an eye template in thermal images. A commercial face recognition software (FaceIt/spl reg/) is used in the evaluation of the various fusion algorithms. Comparison results show that fusion-based face recognition outperforms individual visual or thermal face recognizers under illumination variations and facial expressions. Efforts in the 3D arena are also described. Results of high resolution stereo-based 3D reconstruction of faces are shown and analyzed, in a first approach, then in a second approach, a warping technique is applied to overlay color and thermal textures on 3D mannequin head models, obtained using a laser range scanner.
This work proposes a gain scheduling adaptive control scheme based on fuzzy systems, neural networks and genetic algorithms for nonlinear plants. A fuzzy PI controller is developed, which is a discrete time version of...
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This work proposes a gain scheduling adaptive control scheme based on fuzzy systems, neural networks and genetic algorithms for nonlinear plants. A fuzzy PI controller is developed, which is a discrete time version of a conventional one. Its data base as well as the constant PI control gains are optimally designed by using a genetic algorithm for simultaneously satisfying the following specifications: overshoot and settling time minimizations and output response smoothing. Hence, the optimization problem is a multiobjective one, from which results an optimal fuzzy Pl controller. A neural gain scheduler is designed, by the backpropagation algorithm, to tune the optimal parameters of the fuzzy PI controller at some operating points. Simulation results are shown to demonstrate the efficiency of the proposed structure for a DC servomotor adaptive speed control system used as an actuator of robotic manipulators.
Mobile robots in real-life settings would benefit from being able to localize sound sources. Such a capability can nicely complement vision to help localize a person or an interesting event in the environment, and als...
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Mobile robots in real-life settings would benefit from being able to localize sound sources. Such a capability can nicely complement vision to help localize a person or an interesting event in the environment, and also to provide enhanced processing for other capabilities such as speech recognition. We present a robust sound source localization method in three-dimensional space using an array of 8 microphones. The method is based on a frequency-domain implementation of a steered beamformer along with a probabilistic post-processor. Results show that a mobile robot can localize in real time multiple moving sources of different types over a range of 5 meters with a response time of 200 ms.
We propose a system that gives a mobile robot the ability to separate simultaneous sound sources. A microphone array is used along with a real-time dedicated implementation of geometric source separation and a post-fi...
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We propose a system that gives a mobile robot the ability to separate simultaneous sound sources. A microphone array is used along with a real-time dedicated implementation of geometric source separation and a post-filter that gives us a further reduction of interferences from other sources. We present results and comparisons for separation of multiple non-stationary speech sources combined with noise sources. The main advantage of our approach for mobile robots resides in the fact that both the frequency domain geometric source separation algorithm and the post-filter are able to adapt rapidly to new sources and non-stationarity. Separation results are presented for three simultaneous interfering speakers in the presence of noise. A reduction of log spectral distortion (LSD) and increase of signal-to-noise ratio (SNR) of approximately 10 dB and 14 dB are observed.
A novel approach is presented for determining confidence values for bases called in DNA sequencing. The approach employs fuzzy logic, which forwards flexibility, adaptability and intuition through the use of linguisti...
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A novel approach is presented for determining confidence values for bases called in DNA sequencing. The approach employs fuzzy logic, which forwards flexibility, adaptability and intuition through the use of linguistic variables and fuzzy membership. The proposed fuzzy logic-based method determines the confidence values based on the height, the peakness, and the spacing of the first most likely candidate (the base called) and the peakness and height for the second likely candidate. The technique has been tested on over 3000 ABI 3700 DNA files and the result has shown improved performance over the existing Phred's and ABTs quality value.
This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects,...
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The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dime...
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The Self-Organizing Map (SOM) is an efficient tool for visualizing high-dimensional data. In this paper, an intuitive and effective SOM projection method is proposed for mapping high-dimensional data onto the two-dimensional grid structure with a growing self-organizing mechanism. In the learning phase, a growing SOM is trained and the growing cell structure is used as the baseline framework. In the ordination phase, the new projection method is used to map the input vector so that the input data is mapped to the structure of the SOM without having to plot the weight values, resulting in easy visualization of the data. The projection method is demonstrated on four different data sets, including a 118 patent data set and a 399 checical abstract data set related to polymer cements, with promising results and a significantly reduced network size.
In this research it is claimed that engineering education increases the positivistic tendencies of students regarding to the social problems. A theoretical background is given in the introduction and literature review...
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The purpose of this paper is to present a modified version of the ant colony system (ACS) algorithm. The modified ACS algorithm is faster and it has a better performance than the standard ACS algorithm. We have establ...
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The purpose of this paper is to present a modified version of the ant colony system (ACS) algorithm. The modified ACS algorithm is faster and it has a better performance than the standard ACS algorithm. We have established a set of local rules/modifications, that do improve the performance of the standard ACS and these are reported here.
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