• Title/Summary/Keyword: Object Feature Extraction

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ECoMOT : An Efficient Content-based Multimedia Information Retrieval System Using Moving Objects' Trajectories in Video Data (ECoMOT : 비디오 데이터내의 이동체의 제적을 이용한 효율적인 내용 기반 멀티미디어 정보검색 시스템)

  • Shim Choon-Bo;Chang Jae-Woo;Shin Yong-Won;Park Byung-Rae
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.47-56
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    • 2005
  • A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

A Study of Relationship Derivation Technique using object extraction Technique (개체추출기법을 이용한 관계성 도출기법)

  • Kim, Jong-hee;Lee, Eun-seok;Kim, Jeong-su;Park, Jong-kook;Kim, Jong-bae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.05a
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    • pp.309-311
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    • 2014
  • Despite increasing demands for big data application based on the analysis of scattered unstructured data, few relevant studies have been reported. Accordingly, the present study suggests a technique enabling a sentence-based semantic analysis by extracting objects from collected web information and automatically analyzing the relationships between such objects with collective intelligence and language processing technology. To be specific, collected information is stored in DBMS in a structured form, and then morpheme and feature information is analyzed. Obtained morphemes are classified into objects of interest, marginal objects and objects of non-interest. Then, with an inter-object attribute recognition technique, the relationships between objects are analyzed in terms of the degree, scope and nature of such relationships. As a result, the analysis of relevance between the information was based on certain keywords and used an inter-object relationship extraction technique that can determine positivity and negativity. Also, the present study suggested a method to design a system fit for real-time large-capacity processing and applicable to high value-added services.

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Proposing Shape Alignment for an Improved Active Shape Model (ASM의 성능향상을 위한 형태 정렬 방식 제안)

  • Hahn, Hee-Il
    • Journal of Korea Multimedia Society
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    • v.15 no.1
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    • pp.63-70
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    • 2012
  • In this paper an extension to an original active shape model(ASM) for facial feature extraction is presented. The original ASM suffers from poor shape alignment by aligning the shape model to a new instant of the object in a given image using a simple similarity transformation. It exploits only informations such as scale, rotation and shift in horizontal and vertical directions, which does not cope effectively with the complex pose variation. To solve the problem, new shape alignment with 6 degrees of freedom is derived, which corresponds to an affine transformation. Another extension is to speed up the calculation of the Mahalanobis distance for 2-D profiles by trimming the profile covariance matrices. Extensive experiment is conducted with several images of varying poses to check the performance of the proposed method to segment the human faces.

Sign Language Translation Using Deep Convolutional Neural Networks

  • Abiyev, Rahib H.;Arslan, Murat;Idoko, John Bush
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.631-653
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    • 2020
  • Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

Implementation of Image Processing System for the Defect Inspection of Color Polyethylene (칼라팔레트의 불량 식별을 위한 영상처리 시스템 구현)

  • 김경민;박중조;송명현
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.6
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    • pp.1157-1162
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    • 2001
  • This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

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Extraction of Road Facility Information Using Graphic Solution (지상사진 도해법을 이용한 도로시설물 정보추출)

  • Sohn, Duk-Jae;Lee, Hey-Jin;Lee, Seung-Hwan
    • Journal of Korean Society for Geospatial Information Science
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    • v.10 no.2 s.20
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    • pp.77-85
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    • 2002
  • The intention of this study is to extract the spatial and attribute information of road facility for Geospatial Information System(GIS) using graphic solution. Terrestrial photogrammetry has a lot of possibility for the acquisition of road facility information, which has much convenience in locating camera station, selecting the direction, and taking multiple images of the object at the fixed position. This study intended to develop the technique using single frame images only for the raw image data, being able to apply in the case where comparative high accuracy is not required and rigorous photogrammetric method is not available or rapid acquisition of information is need. As the results, we can find the efficiency in plane feature mapping and determining the dimensions of the road facilities.

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Improvement and Evaluation of the Korean Large Vocabulary Continuous Speech Recognition Platform (ECHOS) (한국어 음성인식 플랫폼(ECHOS)의 개선 및 평가)

  • Kwon, Suk-Bong;Yun, Sung-Rack;Jang, Gyu-Cheol;Kim, Yong-Rae;Kim, Bong-Wan;Kim, Hoi-Rin;Yoo, Chang-Dong;Lee, Yong-Ju;Kwon, Oh-Wook
    • MALSORI
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    • no.59
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    • pp.53-68
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    • 2006
  • We report the evaluation results of the Korean speech recognition platform called ECHOS. The platform has an object-oriented and reusable architecture so that researchers can easily evaluate their own algorithms. The platform has all intrinsic modules to build a large vocabulary speech recognizer: Noise reduction, end-point detection, feature extraction, hidden Markov model (HMM)-based acoustic modeling, cross-word modeling, n-gram language modeling, n-best search, word graph generation, and Korean-specific language processing. The platform supports both lexical search trees and finite-state networks. It performs word-dependent n-best search with bigram in the forward search stage, and rescores the lattice with trigram in the backward stage. In an 8000-word continuous speech recognition task, the platform with a lexical tree increases 40% of word errors but decreases 50% of recognition time compared to the HTK platform with flat lexicon. ECHOS reduces 40% of recognition errors through incorporation of cross-word modeling. With the number of Gaussian mixtures increasing to 16, it yields word accuracy comparable to the previous lexical tree-based platform, Julius.

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Nonlinear Diffusion and Structure Tensor Based Segmentation of Valid Measurement Region from Interference Fringe Patterns on Gear Systems

  • Wang, Xian;Fang, Suping;Zhu, Xindong;Ji, Jing;Yang, Pengcheng;Komori, Masaharu;Kubo, Aizoh
    • Current Optics and Photonics
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    • v.1 no.6
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    • pp.587-597
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    • 2017
  • The extraction of the valid measurement region from the interference fringe pattern is a significant step when measuring gear tooth flank form deviation with grazing incidence interferometry, which will affect the measurement accuracy. In order to overcome the drawback of the conventionally used method in which the object image pattern must be captured, an improved segmentation approach is proposed in this paper. The interference fringe patterns feature, which is smoothed by the nonlinear diffusion, would be extracted by the structure tensor first. And then they are incorporated into the vector-valued Chan-Vese model to extract the valid measurement region. This method is verified in a variety of interference fringe patterns, and the segmentation results show its feasibility and accuracy.

Classification of General Sound with Non-negativity Constraints (비음수 제약을 통한 일반 소리 분류)

  • 조용춘;최승진;방승양
    • Journal of KIISE:Software and Applications
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    • v.31 no.10
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    • pp.1412-1417
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    • 2004
  • Sparse coding or independent component analysis (ICA) which is a holistic representation, was successfully applied to elucidate early auditor${\gamma}$ processing and to the task of sound classification. In contrast, parts-based representation is an alternative way o) understanding object recognition in brain. In this thesis we employ the non-negative matrix factorization (NMF) which learns parts-based representation in the task of sound classification. Methods of feature extraction from the spectro-temporal sounds using the NMF in the absence or presence of noise, are explained. Experimental results show that NMF-based features improve the performance of sound classification over ICA-based features.

Crane Monitoring System for Moving Objects in Safety Lines (크레인 안전선 접근 이동 물체 감시 시스템)

  • Chong, Ui-Pil
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.237-241
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    • 2011
  • Stable operation of an industry crane becomes more important as current industry facilities become larger and operate at higher speeds. This paper proposes implementing a system for monitoring moving objects within safety lines of an industry crane by camera. The cost of implementing such a system is low, since it requires only a webcam and notebook computer. The detection algorithm of moving objects uses the feature extraction method by image differential histograms. The proposed system is robust to variations in the weather and environment. The area of the inside safety lines is considered and shadow removal algorithm is used for good performance of the system. The system is valuable for practical applications in the industry.