Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The ...
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ISBN:
(纸本)9781424420575
Feature extraction and matching is one of the most significant research areas in robot vision. In this paper, we present a new method for motion estimation and mapping using color feature extraction and matching. The proposed method reduces computational cost and has good performance. The experimental result shows that the proposed method not only runs faster but provides accurate result.
Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in ...
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Mean-shift algorithm shows robust performances in various object-tracking technologies including face tracking. Due to its robustness and accuracy, mean-shift algorithm is regarded as one of the best ways to apply in object-tracking technology in computer vision fields. However, it has a drawback of getting into a bottleneck state when faced with a speedy object moving beyond its window size within one image frame interval time. The time required to calculate mean-shift vector could be much lessened with lesser memory when color model is adjusted to the previously known target information. This paper shows the building process of target-adjusted model with a non-uniform quantization. The target color model dealt in this paper is the one used for deriving mean-shift vector. It is a kernel model containing both the color and distance information. This paper gives scheme to efficiently deal with color information in the model. Through a proper selection of color bins, unimportant color values were reduced to a small amount. As a result, the computing time of the mean-shift vector in face-tracking was shortened while maintaining robustness and accuracy.
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, a...
In this paper, a simple method is proposed to evolve artificial neural networks(ANNs) using augmenting weight matrix method(AWMM). ANNs' architecture and connection weights can be evolved simultaneously by AWMM, and their structures incrementally are growing up from minimal structure. It is a non-mating method. It employs 5 mutation operators: add connection, add node, delete connection, delete node, and new initial weight. And the connection weight is trained by the simplified alopex method, which is a correlation based method for solving optimization problem. In AWMM, structural information is encoded to weighting matrix, and the matrix is augmenting as the hidden nodes are added.
The success rate of computerscience and engineering students in private universities are not high. It is helpful to find the model to assist students in registration planning. The objective of this research is to pro...
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The success rate of computerscience and engineering students in private universities are not high. It is helpful to find the model to assist students in registration planning. The objective of this research is to propose the classifier algorithm for building course registration planning model (CRPM) from historical dataset. The algorithm is selected by comparing performances of four classifiers include Bayesian network, C4.5, Decision Forest and NBTree. The dataset were obtained from student enrollments including grade point average (GPA) and grades of undergraduate students whose majors were computerscience or computer engineering. These dataset included grades in each subject of first and second year students from a private university in Thailand. Results showed that NBTree seemed to be the best of four classifiers which had highest prediction power. NBTree was used to generate CRP model which can be used to predict student class of GPA and consider student course sequences for registration planning.
Todaypsilas Information technology supports varieties of e-commerce, in particular on-demand services such as news, message, seminar and presentation speech to message, and 3D Video GIS. Each service can have value-ad...
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Todaypsilas Information technology supports varieties of e-commerce, in particular on-demand services such as news, message, seminar and presentation speech to message, and 3D Video GIS. Each service can have value-added by embedding other hidden-service within the main service, hence promoting value-added to the service. The value-added services are accomplished by using the technique of Multiple Keys and Messages Embedding (MKME), which hidden-contents can be retrieved only by applying the correct corresponding decryption keys This paper presents the design and algorithm for multiple keys and messages embedding on 3D Video GIS, based on Steganography concept. The quality of the resulting product was also investigated. The main data used is geospatial video, which is primarily used by the elderly and disables people so that they can feel the surroundings on their desktop while sitting at home.
Distance learning is a learning style that can overcome the limitation of time and space. Because of the distance, teachers can not handle the student's learning situation, and they do not know whether the student...
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Distance learning is a learning style that can overcome the limitation of time and space. Because of the distance, teachers can not handle the student's learning situation, and they do not know whether the student is attentive, drowsy or absent. If teachers can know the student's affective state, they can overcome the difficult. The research applies the image recognition technologies to capture the face images of students when they are learning and analyzes their face features to evaluate the student's affective state by Fuzzy Integral. Finally, teachers can monitor the student's behavior by the detection results on the system interface.
The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registere...
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ISBN:
(纸本)9781424414895
The objective of this study is to propose a model for planning course registration by using a data mining technique: Bayesian network. The proposed model can be used to predict the sequences of courses to be registered by undergraduate students whose majors are computerscience or engineering. The data set was obtained from student enrollments and include GPA and grades in each subject for first and second year students from a private university in Thailand. Evaluations show that the predictive power of this model is acceptable. The implications from this studypsilas findings suggest that the model can be applied for advising students in planning courses to be registered in each semester. Further, the model appears to be useful for improving curriculum development in order to fit both studentspsila and university requirements.
Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he ca...
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Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he can avoid situations in which students are inattentive. Many studies have analyzed student attentiveness by the applying of image detection technologies. If this mechanism can be applied to in-class learning, it will help teachers keep students attentive, and reduce teacher load during class. This study mainly applies fuzzy logic analysis of student facial images when participating in class. Applying fuzzy logic can prevent erroneous judgments associated with a single term, and help teachers deal with student attentiveness.
This paper discusses phase noise characteristics of an Fr oscillator focusing on a signal output position. Oscillation circuits can be divided into an amplifier and a feedback circuit. We compared that phase noise cha...
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Clinical guidelines usually need to be adapted to fit local practice before they can be actually used by clinicians. Reasons for adaptation include variations of institution setting such as type of practice and locati...
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