A methodology for motion analysis and hand tracking based on adaptive probabilistic models is presented. This is done by integrating a deterministic clustering framework and a particle filter together in real time. Th...
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A methodology for motion analysis and hand tracking based on adaptive probabilistic models is presented. This is done by integrating a deterministic clustering framework and a particle filter together in real time. The skin color of a human hand is firstly segmented. A Bayesian classifier and an adaptive process are utilized for determining skin color probabilities. The methodology enables us to deal with luminance changes. After that, we determine the probabilities of the fingertips by using semicircle models for fitting curves to fingertips. Following this, the deterministic clustering algorithm is utilized to search for regions of interest, and then the Sequential Monte Carlo is also performed to track the fingertips efficiently. Representative experimental results are also included to ensure workability of the proposed framework. Several issues about using the presented method in embedded systems are discussed. The method presented can be used to further develop the associated applications of embedded robotic and virtual reality.
Data mining is one of the interesting research areas in database technology. In data mining, a cluster is a set of data objects that are similar to one another with in a cluster and are different to the entities in th...
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ISBN:
(纸本)9781479915941;9781479915958
Data mining is one of the interesting research areas in database technology. In data mining, a cluster is a set of data objects that are similar to one another with in a cluster and are different to the entities in the former clusters. clustering is the efficient method in data mining in order to process huge data sets. The core methodology of clustering is used in many domains like academic result analysis of institutions. Also, the methods are very well suited in machine learning, clustering in medical dataset, pattern recognition, image mining, information retrieval and bioinformatics. The clustering algorithms are categorized based upon different research phenomenon. Varieties of algorithms have recently occurred and were effectively applied to real-life data mining problems. This survey mainly focuses on partition based clustering algorithms namely k-Means, k-Medoids and Fuzzy c-Means In particular, they applied mostly in medical data sets. The importance of the survey is to explore the various applications in different domains.
Nowadays, long wait, cancellations and resource overload frequently occur in healthcare, especially in those sectors related to the patients passing through the operating theatre in both United States and the European...
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The subtractive clustering algorithm (SC) is a popular method for data clustering. But the radius of each cluster is an important factor which affects the performances of clustering results. This paper proposes an obj...
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ISBN:
(纸本)9781467361996
The subtractive clustering algorithm (SC) is a popular method for data clustering. But the radius of each cluster is an important factor which affects the performances of clustering results. This paper proposes an objective function for the genetic algorithm to estimate the optimal value of this parameter. Two experiments show that the proposed method can automatically obtain this parameter for the subtractive clustering algorithm.
C-average algorithm (also known as the FCM algorithm) is a clustering algorithm based on partition. The idea of the algorithm is making is divided into clusters with the similarity between objects as large as possible...
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ISBN:
(纸本)9781479928606
C-average algorithm (also known as the FCM algorithm) is a clustering algorithm based on partition. The idea of the algorithm is making is divided into clusters with the similarity between objects as large as possible, and the similarity between objects of different clusters as small as possible. As the algorithm is simple, easy to implement and computer clustering effect, etc., makes this algorithm in many fields has been widely applied. This paper focuses principles of FCM algorithm, the algorithm steps and its problems were described in detail and propose an improved algorithm.
Embedded Internet has preset functions and strong adaptability, which can be used in household appliances, medical equipment, and industrial machinery and so on. Through the method of embedded network, it completely c...
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ISBN:
(纸本)9783038351153
Embedded Internet has preset functions and strong adaptability, which can be used in household appliances, medical equipment, and industrial machinery and so on. Through the method of embedded network, it completely changed the way of people live. In this paper we use clustering algorithm to improve the embedded network system, and use JSP technology to enhance the real-time and interactive of system, develop the aerobics visualization movement system, which realizes the interactive action between teachers and students. In order to test the performance of the system, we use AMBE-2000 as communication module to test the video compression and processing functions of embedded system. The results show that the compression ratio is big, the flow is small, and compression time is short. It is a stable and reliable network system. It provides a new method for embedded computer system in sports teaching.
Web logs are user transactions stored in the web log files, and it is unstructured for mining knowledge. Since the usage of internet has increased, data in the web log file is very important for finding user navigatio...
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ISBN:
(纸本)9781479941902
Web logs are user transactions stored in the web log files, and it is unstructured for mining knowledge. Since the usage of internet has increased, data in the web log file is very important for finding user navigational behavior. Accurate web log mining extracts results and efficient navigational patterns that are crucial for tuning websites and consequently helping in visitor retention. Web log mining task is to extract some hidden knowledge which is not done by any other conventional data mining algorithms. In order to produce good result web log mining depends on some quality input. Hence the first challenge is to perform effective data cleaning and preprocessing, and the second challenge is to improve the efficiency of online prediction. This paper proposes an enhancement to web log mining and to evaluate its performance to fulfill the aforementioned challenges.
Outlier detection has a wide range of applications. In this paper we present a new method for detecting outliers, focused on reducing the number of computations. Our method operates on two phases and uses one pruning ...
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ISBN:
(纸本)9781479932641
Outlier detection has a wide range of applications. In this paper we present a new method for detecting outliers, focused on reducing the number of computations. Our method operates on two phases and uses one pruning strategy. Objective is to remove the points which are considered to be inliers. In the first phase a clustering algorithm is applied to partition the data into clusters and make an estimate to prune the clusters, in the second phase we apply a outlier score function to dictate the outliers. The experimental results using real datasets demonstrate the superiority of our method over existing outlier detection method.
Network splitting requires novel routing scheme different from traditional storage and forwarding manner. In the split wireless sensor networks, message ferrying method can be introduced to provide normal communicatio...
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ISBN:
(纸本)9781479920303
Network splitting requires novel routing scheme different from traditional storage and forwarding manner. In the split wireless sensor networks, message ferrying method can be introduced to provide normal communication for network within tolerable delay. The definition of network delay and packet loss rate in such routing protocol was brought out. The computation method of indexes was also provided. Simulation experiment addresses to the effect of transmission rate and node cache space on average network delay and packet loss rate. Simulation results show that transmission rate of nodes and ferry can enlarge delay, while cache space can reduce packet loss rate.
This paper examines the method of road surface recognition, based on the analysis of backscattered radar and ultrasonic signals. The results demonstrate that the use of cluster analysis allows for reliable discriminat...
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ISBN:
(纸本)9782874870378
This paper examines the method of road surface recognition, based on the analysis of backscattered radar and ultrasonic signals. The results demonstrate that the use of cluster analysis allows for reliable discrimination of various on-road and off-road surfaces of practical interest.
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