• 제목/요약/키워드: object-based approach

검색결과 868건 처리시간 0.032초

구조해석에서 객체지향 방법론의 도입 (Application of Object-Oriented Methodology for Structural Analysis and Design)

  • 이주영;김홍국;이병해
    • 한국전산구조공학회:학술대회논문집
    • /
    • 한국전산구조공학회 1995년도 봄 학술발표회 논문집
    • /
    • pp.160-169
    • /
    • 1995
  • This study presents an application of object-oriented methodology for structural dcsign process. A prototype system of integrated a structural design system is developed by introducing a structural analysis object model(SAOM) and structural design object model(SDOM). The SAOM module. which is modeled as a part of structural member, performs structural analysis using FEM approach and the SDOM module checks structural members based on Korea steel design standard. Above mentionedmodelsareabstraclencapsulatibleandreusable.

  • PDF

객체 분할과 HAQ 알고리즘을 이용한 내용 기반 영상 검색 특징 추출 (Feature Extraction Of Content-based image retrieval Using object Segmentation and HAQ algorithm)

  • 김대일;홍종선;장혜경;김영호;강대성
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
    • /
    • pp.453-456
    • /
    • 2003
  • Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

  • PDF

확률적 표본화와 배경 차분을 이용한 비디오 객체 추적 (Visual Tracking Using Monte Carlo Sampling and Background Subtraction)

  • 김현철;백준기
    • 대한전자공학회논문지SP
    • /
    • 제48권5호
    • /
    • pp.16-22
    • /
    • 2011
  • 본 논문에서는 배경 차분에 의해 객체를 검출하고 확률적으로 표본화된 입자 필터링(particle filtering)기법을 사용한 다중객체 추적 기법을 제안한다. 확률적으로 표본화된 입자들을 사용하여 다중 객체에 독립적으로 적용할 때 발생하는 계산 복잡도(computational complexity)를 감소시키는 동시에 안정적인 추적을 가능하게 하였다. 객체의 색상정보를 사용한 히스토그램 분포에 의한 관측 모델(observation model)을 구성하고 객체의 움직임 정보를 위해 동적 모델을 공식화하여 영상을 해석하였다. 전체적인 추적 시스템은 베이시언 최대 우도 기법(Bayesian maximum likelihood method)을 근간으로 하되, 입자 필터링을 객체 추적에 적용하여 실용적인 현실 객체 추적 상황에도 강건하게 대처할 수 있음을 실험을 통해서 증명하였다.

Anomalous Event Detection in Traffic Video Based on Sequential Temporal Patterns of Spatial Interval Events

  • Ashok Kumar, P.M.;Vaidehi, V.
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제9권1호
    • /
    • pp.169-189
    • /
    • 2015
  • Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

증강현실 기반 상호작용과 시뮬레이션을 이용한 휴대용 전자제품의 설계품평 (Design Evaluation of Portable Electronic Products Using AR-Based Interaction and Simulation)

  • 박형준;문희철
    • 한국CDE학회논문집
    • /
    • 제13권3호
    • /
    • pp.209-216
    • /
    • 2008
  • This paper presents a novel approach to design evaluation of portable consumer electronic (PCE) products using augmented reality (AR) based tangible interaction and functional behavior simulation. In the approach, the realistic visualization is acquired by overlaying the rendered image of a PCE product on the real world environment in real-time using computer vision based augmented reality. For tangible user interaction in an AR environment, the user creates input events by touching specified regions of the product-type tangible object with the pointer-type tangible object. For functional behavior simulation, we adopt state transition methodology to capture the functional behavior of the product into a markup language-based information model, and build a finite state machine (FSM) to controls the transition between states of the product based on the information model. The FSM is combined with AR-based tangible objects whose operation in the AR environment facilitates the realistic visualization and functional simulation of the product, and thus realizes faster product design and development. Based on the proposed approach, a product design evaluation system has been developed and applied for the design evaluation of various PCE products with highly encouraging feedbacks from users.

3차원 측정자료부터 자유곡면의 가공을 위한 공구경로생성 (Generating Cartesian Tool Paths for Machining Sculptured Surfaces from 3D Measurement Data)

  • 고병철;김광수
    • 대한산업공학회지
    • /
    • 제19권3호
    • /
    • pp.123-137
    • /
    • 1993
  • In this paper, an integrated approach is proposed to generate gouging-free Cartesian tool paths for machining sculptured surfaces from 3D measurement data. The integrated CAD/CAM system consists of two modules : offset surface module an Carteian tool path module. The offset surface module generates an offset surface of an object from its 3D measurement data, using an offsetting method and a surface fitting method. The offsetting is based on the idea that the envelope of an inversed tool generates an offset surface without self-intersection as the center of the inversed tool moves along on the surface of an object. The surface-fitting is the process of constructing a compact representation to model the surface of an object based on a fairly large number of data points. The resulting offset surtace is a composite Bezier surface without self-intersection. When an appropriate tool-approach direction is selected, the tool path module generates the Cartesian tool paths while the deviation of the tool paths from the surface stays within the user-specified tolerance. The tool path module is a two-step process. The first step adaptively subdivides the offset surface into subpatches until the thickness of each subpatch is small enough to satisfy the user-defined tolerance. The second step generates the Cartesian tool paths by calculating the intersection of the slicing planes and the adaptively subdivided subpatches. This tool path generation approach generates the gouging-free Cartesian CL tool paths, and optimizes the cutter movements by minimizing the number of interpolated points.

  • PDF

MBR을 이용한 실용적 공간 데이터 관리 (A Practical Approach to Spatial Object Indexing Using Minimum Bounding Rectangles)

  • 이재호
    • 한국정보과학회:학술대회논문집
    • /
    • 한국정보과학회 1999년도 가을 학술발표논문집 Vol.26 No.2 (1)
    • /
    • pp.177-179
    • /
    • 1999
  • We present a simple and efficient spatial object indexing scheme based on the minimum bounding rectangles (MBR) of the objects for use in applications in geographic information system (GIS). We also provide the rationale behind the simple indexing scheme instead of other complex hierarchical indexing approaches such as the R-tree and its variants.

  • PDF

Object Classification based on Weakly Supervised E2LSH and Saliency map Weighting

  • Zhao, Yongwei;Li, Bicheng;Liu, Xin;Ke, Shengcai
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제10권1호
    • /
    • pp.364-380
    • /
    • 2016
  • The most popular approach in object classification is based on the bag of visual-words model, which has several fundamental problems that restricting the performance of this method, such as low time efficiency, the synonym and polysemy of visual words, and the lack of spatial information between visual words. In view of this, an object classification based on weakly supervised E2LSH and saliency map weighting is proposed. Firstly, E2LSH (Exact Euclidean Locality Sensitive Hashing) is employed to generate a group of weakly randomized visual dictionary by clustering SIFT features of the training dataset, and the selecting process of hash functions is effectively supervised inspired by the random forest ideas to reduce the randomcity of E2LSH. Secondly, graph-based visual saliency (GBVS) algorithm is applied to detect the saliency map of different images and weight the visual words according to the saliency prior. Finally, saliency map weighted visual language model is carried out to accomplish object classification. Experimental results datasets of Pascal 2007 and Caltech-256 indicate that the distinguishability of objects is effectively improved and our method is superior to the state-of-the-art object classification methods.

A Study on Kohenen Network based on Path Determination for Efficient Moving Trajectory on Mobile Robot

  • Jin, Tae-Seok;Tack, HanHo
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제10권2호
    • /
    • pp.101-106
    • /
    • 2010
  • We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

UML 정적구조 다이아그램으로부터 LOTOS 명세 생성 (Generating LOTOS Specifications from UML Static Structure Diagrams)

  • 김철홍;안유환;이원천
    • 한국정보처리학회논문지
    • /
    • 제6권12호
    • /
    • pp.3500-3513
    • /
    • 1999
  • 객체지향 기법과 정형 기법은 미래의 소프트웨어 공학 분야에 지대한 영향을 미칠 잠재력을 가진 두 갈래의 큰 영역으로 인식되고 있다. 따라서 이 두 영역의 접목 "객체지향 기술을 이용한 시스템 명세의 정형적 접근"은 빠른 속도로 성장하고 있으며 많은 연구결과를 산출하고 있다. LOTOS는 객체 기반 접근에 매우 적절하나, 완전한 객체지향 접근 방법을 제공하기 위하여 일반화(상속과 다형성)를 모델링할 수 있어야 한다. 이러한 주제를 연구해온 대부분의 연구자들은 LOTOS을 확장을 제안하였다. 본 논문은 ISO 8807 LOTOS로의 변환에 관심을 두며, 이러한 연구 동향의 일환으로 UML 정적구조 다이아그램으로부터 LOTOS 명세를 생성하는 방법을 제안한다.

  • PDF