• 디지털산업정보학회논문지
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• 제9권1호
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• pp.141-150
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• 2013

This study proposes technology using Active Shape Model to track the object separating it by depth-sensors. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust object can be extracted. The proposed algorithm removes the horizontal component from the information of the initial depth map and separates the object using the vertical component. In addition, it is also a more efficient morphology, and labeling to perform image correction and object extraction. By applying Active Shape Model to the information of an extracted object, it can track the object more robustly. Active Shape Model has a robust feature-to-object occlusion phenomenon. In comparison to visual camera-based object tracking algorithms, the proposed technology, using the existing depth of the sensor, is more efficient and robust at object tracking. Experimental results, show that the proposed ASM-based algorithm using depth sensor can robustly track objects in real-time.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제7권6호
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• pp.630-640
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• 2001

본 논문에서는 공유 객체 모델 기반의 P2P(Peer-to-Peer) 애플리케이션을 개발하기 위한 프레임워크인 ObjectPeerWork를 설계 및 구현한다. 공유 객체 모델은 자원 관리 기능들을 자원에 포함시킴으로써 관리를 위한 컴퓨팅 파워의 저하를 막고, 보안 문제를 개선함으로써 공유 자원에 대한 신뢰도를 향상시킬 수 있다. 또한, 공유 객체 모델은 분산 컴포넌트 기반의 요청 중계 관리자 및 모듈 컨테이너를 통하여 확장이 가능한 모델이다. 이러한 공유 객체 모델에 기만한 ObjectPeerWork는 일반적인 P2P 모델의 문제점들을 개선하여 기업 내 정보시스템 구축과 컴퓨팅 파워의 분산 및 자원의 효율적인 관리를 가능하게 하는 프레임워크이다.

• 대한임베디드공학회논문지
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• 제17권5호
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• pp.289-296
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• 2022

In this paper, we developed a deep learning-based recyclable object detection model. The model is developed based on YOLOv5 that is a one-stage detector. The deep learning model detects and classifies the recyclable object into 7 categories: paper, carton, can, glass, pet, plastic, and vinyl. We propose two methods for recyclable object detection models to solve problems during training. Bounding Box CutMix solved the no-objects training images problem of Mosaic, a data augmentation used in YOLOv5. Standardized Distance-based IoU replaced DIoU using a normalization factor that is not affected by the center point distance of the bounding boxes. The recyclable object detection model showed a final mAP performance of 0.91978 with Bounding Box CutMix and 0.91149 with Standardized Distance-based IoU.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2009년도 IWAIT
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• pp.223-228
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• 2009

We propose an on-line machine learning approach for object recognition, where new images are continuously added and the recognition decision is made without delay. Random forest (RF) classifier has been extensively used as a generative model for classification and regression applications. We extend this technique for the task of building incremental component-based detector. First we employ object descriptor model based on bag of covariance matrices, to represent an object region then run our on-line RF learner to select object descriptors and to learn an object classifier. Experiments of the object recognition are provided to verify the effectiveness of the proposed approach. Results demonstrate that the propose model yields in object recognition performance comparable to the benchmark standard RF, AdaBoost, and SVM classifiers.

• 지능정보연구
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• 제9권3호
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• pp.99-115
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• 2003

본 논문은 지식 기반 객체지 향 공간 데이터베이스시스템 KOBOS를 제안한다. 객체지향 공간 데이터베이스 시스템의 데이터 모델링과 근접 질의답변에 지식기반 접근법을 도입한다. 공간객체와 근접 공간 연산자를 다루기 위해 다음과 같은 세 단계 객체지향 데이터 모델을 제안하고 있다: (1) 공간 형상 모델; (2) 공간 객체 모델: (3) 내부 기술 모델. 근접 공간 연산자의 범위는 공간 타입 추상 계층으로 알 수 있다. 또한 객체지향 공간 질의어인 SOQL을 제안한다. SOQL은 공간 객체의 다양한 출력과 공간 및 비 공간 객체의 검색을 수행할 수 있는 통합 기능을 제공해준다. 효율적인 혼합 질의 처리를 위하여, 하향 공간 질의 처리 방법을 이용하여 처리해 준다.

• 한국통신학회논문지
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• 제23권9A호
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• pp.2258-2270
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• 1998

Recently, the distributed processing environments provide various open multimedia serivces through telecommunication network and have been developing into information networking structure based on object oriented concepts and distributed systems which can apply new services with a few changes the existing networks. This paper proposes the object group model which is the collection of objects and can functionally and efficiently manage the individual object. this paper presents the analysis of the requirement and the function specifications to propose the object group model, and depicts the functional structure in details using its analysis. The goal of this paper is to decrease the complexity of the object's management and to voercome the limitations of among the components of object group for management and service functions based on our proposed the object group model and show interaction procedures to eTD (event tracing diagram)s and finally we design the object group model by TINA-ODL.

• 드라이브 ㆍ 컨트롤
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• 제16권2호
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• ETRI Journal
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• 제34권3호
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• pp.399-409
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• 2012

In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1113-1116
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• 2009

The attempt to use a 3D model each field such as design, structure, construction, facilities, and estimation in the construction project has recently increased more and more while BIM (Building Information Modeling) that manages the process of generating and managing building data has risen during life cycle of a construction project. While the 2D Drawing based work of each field is achieved in the already existing construction project, the BIM based construction project aims at accomplishing 3D model based work of each field efficiently. Accordingly, the solution that fits 3D model based work of each field and supports plans in order to efficiently accomplish the relevant work is demanded. The estimation, one of the fields of the construction project, has applied BIM to calculate quantity and cost of the building materials used to construction works after taking off building quantity information from the 3D model by a item for a Quantity Take-off grouping the materials relevant to a 3D object. A 3D based estimation program has been commonly used in abroad advanced countries using BIM. The program can only calculate quantity related to one 3D object. In other words, it doesn't support the take-off process considering quantity of a contiguous object. In case of temporary materials used in the frame construction, there are instances where quantity is different by the contiguous object. For example, the formwork of the temporary materials quantity is changed by dimensions of the contiguous object because formwork of temporary materials goes through the quantity take-off process that deduces quantity of the connected object when different objects are connected. A worker can compulsorily adjust quantity so as to recognize the different object connected to the contiguous object and deduces quantity, but it mainly causes the confusion of work because it must complexly consider quantity of other materials related to the object besides. Therefore, this study is to propose the solution that automates the formwork 3D modeling to efficiently accomplish the quantity take-off of formwork by preventing the confusion of the work which is caused by the quantity deduction process between the contiguous object and the connected object.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 3부
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• pp.19-24
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• 2008

본 논문은 원격제어(teleoperation)시스템에서 카메라로부터의 실시간 영상정보를 이용하여 조작대상이 되는 물체의 물리기반모델(physically-based model)을 만들고 이를 기반으로한 햅틱 렌더링 알고리즘의 개발에 관한 것이다. CCD 카메라를 통한 영상정보와 물성치(mechanical properties)를 이용하여 변형체(deformable object)의 물리적 기반 모델이 구현되고 햅틱장치로 조종되는 평면 로봇(planar robot)을 제어하여 변형체에 변형을 가하면 구현된 물리적 모델에 의해 햅틱 피드백을 위한 반력값이 계산된다. 스네이크 알고리즘을 이 용하여 영상정보로부터 변형체의 외형정보(geometry information)를 추출하며, 변형체의 경계(boundary)에서의 반력값을 계산하기 위해 경계요소법(boundary element method)을 사용한다. 제안된 햅틱 렌더링 알고리즘을 이용하여 원격조작간에 힘센서를 사용하지 않고 사용자에게 햅틱 피드백을 제공할 수 있다.