• Title/Summary/Keyword: Principle component analysis

Search Result 385, Processing Time 0.026 seconds

Classification of Sitting Position by IMU Built in Neckband for Preventing Imbalance Posture (불균형 자세 예방용 IMU 내장 넥밴드를 이용한 앉은 자세 분류)

  • Ma, S.Y.;Shim, H.M.;Lee, S.M.
    • Journal of rehabilitation welfare engineering & assistive technology
    • /
    • v.9 no.4
    • /
    • pp.285-291
    • /
    • 2015
  • In this paper, we propose a classification algorithm for postures of sitting person by using IMU(inertial measurement unit). This algorithm uses PCA(principle component analysis) for decreasing the number of feature vectors to three and SVM(support vector machine) with RBF(radial basis function) kernel for classifying posture types. In order to collect the data, we designed neckband-shaped earphones with IMU, and applied it to three subjects who are healthy adults. Subjects were experimented three sitting postures, which are neutral posture, smartphoning, and writing. As the result, our PCA-SVM algorithm showed 95% confidence while the dimension of the feature vectors was reduced to 25%.

  • PDF

Similar Video Detection Method with Summarized Video Image and PCA (요약 비디오 영상과 PCA를 이용한 유사비디오 검출 기법)

  • Yoo, Jae-Man;Kim, Woo-Saeng
    • Journal of Korea Multimedia Society
    • /
    • v.8 no.8
    • /
    • pp.1134-1141
    • /
    • 2005
  • With ever more popularity of video web-publishing, popular content is being compressed, reformatted and modified, resulting in excessive content duplication. Such overlapped data can cause problem of search speed and rate of searching. However, duplicated data on other site can provide alternatives while specific site cause problem. This paper proposes the efficient method, for retrieving. similar video data in large database. In this research we have used the method to compare summarized video image instead of the raw video data, and detected similar videos through clustering in that dimension feature vector through PCA(principle component analysis). We show that our proposed method is efficient and accurate through our experiment.

  • PDF

Lip Shape Representation and Lip Boundary Detection Using Mixture Model of Shape (형태계수의 Mixture Model을 이용한 입술 형태 표현과 입술 경계선 추출)

  • Jang Kyung Shik;Lee Imgeun
    • Journal of Korea Multimedia Society
    • /
    • v.7 no.11
    • /
    • pp.1531-1539
    • /
    • 2004
  • In this paper, we propose an efficient method for locating human lips. Based on Point Distribution Model and Principle Component Analysis, a lip shape model is built. Lip boundary model is represented based on the concatenated gray level distribution model. We calculate the distribution of shape parameters using Gaussian mixture. The problem to locate lip is simplified as the minimization problem of matching object function. The Down Hill Simplex Algorithm is used for the minimization with Gaussian Mixture for setting initial condition and refining estimate of lip shape parameter, which can refrain iteration from converging to local minima. The experiments have been performed for many images, and show very encouraging result.

  • PDF

Design of RBFNNs Pattern Classifier Realized with the Aid of PSO and Multiple Point Signature for 3D Face Recognition (3차원 얼굴 인식을 위한 PSO와 다중 포인트 특징 추출을 이용한 RBFNNs 패턴분류기 설계)

  • Oh, Sung-Kwun;Oh, Seung-Hun
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.63 no.6
    • /
    • pp.797-803
    • /
    • 2014
  • In this paper, 3D face recognition system is designed by using polynomial based on RBFNNs. In case of 2D face recognition, the recognition performance reduced by the external environmental factors such as illumination and facial pose. In order to compensate for these shortcomings of 2D face recognition, 3D face recognition. In the preprocessing part, according to the change of each position angle the obtained 3D face image shapes are changed into front image shapes through pose compensation. the depth data of face image shape by using Multiple Point Signature is extracted. Overall face depth information is obtained by using two or more reference points. The direct use of the extracted data an high-dimensional data leads to the deterioration of learning speed as well as recognition performance. We exploit principle component analysis(PCA) algorithm to conduct the dimension reduction of high-dimensional data. Parameter optimization is carried out with the aid of PSO for effective training and recognition. The proposed pattern classifier is experimented with and evaluated by using dataset obtained in IC & CI Lab.

Application of Substructure Synthesis Method for Analysis of Acoustic System (음향계의 해석을 위한 부분구조합성법의 적용)

  • 오재응;고상철;조용구
    • Journal of KSNVE
    • /
    • v.7 no.5
    • /
    • pp.737-746
    • /
    • 1997
  • The substructure synthesis method is used for making it easy to analyze vibration systems generally in vibration field. In the past, this method has been to be used mainly because of shortage of computer memory and CPU time. But recently this method is used for analyzing complex structure or identifying the characteristics of systems precisely. The purpose of this study is to develop acoustic substructure synthesis method that can be applied to acoustic modal analysis of complex acoustic systems. Acoustic modal analysis method to be introduced here is a method that analyze acoustic natural mode shape of the complex acoustic system by the principle of CMS(component mode synthesis method). This paper describes the acoustic modal analysis of the acoustic finite element model of simple expansion pipe by acoustic substructure synthesis method. The resutls of acoustic modal analysis analyzed by Acoustic substructure synthesis method and the results by FEM(finite element method) shows good agreement.

  • PDF

Analysis of Volatile Compounds using Electronic Nose and its Application in Food Industry (전자코를 이용한 휘발성분의 분석과 식품에의 이용)

  • Noh, Bong-Soo
    • Korean Journal of Food Science and Technology
    • /
    • v.37 no.6
    • /
    • pp.1048-1064
    • /
    • 2005
  • Detection of specific compounds influencing food flavor quality is not easy. Electronic nose, comprised of electronic chemical sensors with partial specificity and appropriate pattern recognition system, is capable of recognizing simple and complex volatiles. It provides fast analysis with simple and straightforward results and is best suited for quality control and process monitoring of flavor in food industry. This review examines application of electronic nose in food analysis with brief explanation of its principle. Characteristics of different sensors and sensor drift. and solutions to related problems are reviewed. Applications of electronic nose in food industry include monitoring of fermentation process and lipid oxidation, prediction of shelf life, identification of irradiated volatile compounds, discrimination of food material origin, and quality control of food and processing by principal component analysis and neural network analysis. Electronic nose could be useful for quality control in food industry when correlating analytical instrumental data with sensory evaluation results.

A Study of Development and Product ion Technology for Camcoder Iris Assembly (캠코더용 Iris Assembly의 국산화 및 생산 기술 개발 사례)

  • Ko, Jong-Sun
    • Proceedings of the KIEE Conference
    • /
    • 1996.07a
    • /
    • pp.250-252
    • /
    • 1996
  • In this paper, the principle of operation. the part characteristic, characteristic of component movement, analysis are carried out for camcoder iris assembly which is one of the important element component in Video large projection TV instrument, and some Know-how for development of element component is also included. The magnetic field circuit for the small and simple structure with low power consumption is introduced and new materials of yoke for small motor system is suggested. Especially, the relation with remained magnetic field and operation duration time is analyzed by experimental results. Some problems of nonlinear torque characteristics include to obtain the simple and low cost structure in domestic production of element component is analyzed. Furthermore, development procedure is suggested for iris assembly and some methods to reduce the burr with some check points for small precise accessories are explained.

  • PDF

Interspecific Relationship of Polygonatum Species Collected from Gyeongnam Area Using Cluster Analysis (경남지역 둥굴레속의 Cluster 분석에 의한 종간 유연관계)

  • Shim, Jae-Suk;Park, Jeong-Min;Jeon, Byong-Sam;Kang, Jin-Ho
    • Korean Journal of Medicinal Crop Science
    • /
    • v.13 no.1
    • /
    • pp.30-34
    • /
    • 2005
  • Polygonatum species are a useful medical crop in Korea but basic study in the species was not well conducted. The study was carried out to analyse genetic diversity and intraspecific relationship of 47 Polygonatum species collected from Gyeongnam province. Their analysis was done through principle component analysis and average linkage cluster analysis with their twelve morphological traits. The result of principle component analysis showed the Prin 1, Prin 2 and Prin 3 represented 79% of total variation. By the 0.7 average distance of the cluster analysis and the calculated Euclidian distance, the 47 collected species were grouped into five groups. Group I included 22 collected species representing P. ordoratum var. pluriflorum, group II did 5 ones representing P. involucratum, group III was divided into two subclasses, 2 species including P. inflatum and 7 species including P. thunbergii, group IV also consisted of 2 subclasses, a species similar to P. thunbergii and P.involucratum, respectively, and finally group V included 8 species representing P.lasianthum var. coreanum. meaning that the useful germplasms can be collected from relatively small area.

Photomosaics Using Principal Component Analysis (주성분 분석을 사용한 포토모자이크)

  • Chun, Young-Jae;Oh, Kyoung-Su;Cho, Sung-Hyun
    • Journal of Korea Game Society
    • /
    • v.11 no.1
    • /
    • pp.139-146
    • /
    • 2011
  • We propose a photomosaic method using PCA(Principal Component Analysis), which uses PCA results to find the most similar candidate fast and correctly. When two images are projected onto a certain principal component, if their coefficients are similar, they are also likely to be similar. Thus our photomosaic method using PCA can take care of both colors and shapes of images. Our method using coefficient comparison is faster than the one using all color comparison and more correct than the one using average comparison. Our hardware accelerated photomosaic algorithm can handle video images in real-time.

Probabilistic K-nearest neighbor classifier for detection of malware in android mobile (안드로이드 모바일 악성 앱 탐지를 위한 확률적 K-인접 이웃 분류기)

  • Kang, Seungjun;Yoon, Ji Won
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.25 no.4
    • /
    • pp.817-827
    • /
    • 2015
  • In this modern society, people are having a close relationship with smartphone. This makes easier for hackers to gain the user's information by installing the malware in the user's smartphone without the user's authority. This kind of action are threats to the user's privacy. The malware characteristics are different to the general applications. It requires the user's authority. In this paper, we proposed a new classification method of user requirements method by each application using the Principle Component Analysis(PCA) and Probabilistic K-Nearest Neighbor(PKNN) methods. The combination of those method outputs the improved result to classify between malware and general applications. By using the K-fold Cross Validation, the measurement precision of PKNN is improved compare to the previous K-Nearest Neighbor(KNN). The classification which difficult to solve by KNN also can be solve by PKNN with optimizing the discovering the parameter k and ${\beta}$. Also the sample that has being use in this experiment is based on the Contagio.