• 대한임베디드공학회논문지
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• 제17권2호
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• pp.77-83
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• 2022

In this paper, the two-stage object detection approach is proposed to implement a deep learning-based label inspection system on edge computing environments. Since the label printed on the products during the production process contains important information related to the product, it is significantly to check the label information is correct. The proposed system uses the lightweight deep learning model that able to employ in the low-performance edge computing devices, and the two-stage object detection approach is applied to compensate for the low accuracy relatively. The proposed Two-Stage object detection approach consists of two object detection networks, Label Area Detection Network and Character Detection Network. Label Area Detection Network finds the label area in the product image, and Character Detection Network detects the words in the label area. Using this approach, we can detect characters precise even with a lightweight deep learning models. The SF-YOLO model applied in the proposed system is the YOLO-based lightweight object detection network designed for edge computing devices. This model showed up to 2 times faster processing time and a considerable improvement in accuracy, compared to other YOLO-based lightweight models such as YOLOv3-tiny and YOLOv4-tiny. Also since the amount of computation is low, it can be easily applied in edge computing environments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.5-7
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• 1996

We propose a triangulation method based on stereo vision angles. We setup stereo vision systems which extract the depth information to a moving object by detecting a moving object using difference image method and obtaining the depth information by the triangulation method based on stereo vision angles. The feature point of a moving object is used the geometrical center of the moving object, and the proposed vision system has the accuracy of 0.2mm in the range of 400mm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.141-144
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• 2002

This paper describes a new feature based tracking system that can track moving objects with a pan-tilt camera. We extract corner features of the scene and tracks the features using filtering, The global motion energy caused by camera movement is eliminated by finding the maximal matching position between consecutive frames using Pyramidal template matching. The region of moving object is segmented by clustering the motion trajectories and command the pan-tilt controller to follow the object such that the object will always lie at the center of the camera. The proposed system has demonstrated good performance for several video sequences.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.427-430
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• 2019

Object detection is applied in various field. Autonomous driving, surveillance, OCR(optical character recognition) and aerial image etc. We will look at the algorithms that are using to object detect. These algorithms are divided into two methods. The one is R-CNN algorithms [2], [5], [6] which based on region proposal. The other is YOLO [7] and SSD [8] which are one stage object detector based on regression/classification.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2003년도 추계학술대회 및 정기총회
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• pp.19-25
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• 2003

Since container throughput is continually increasing, the main issues facing decision-makers at port container terminals are how to expand the existing container terminals and construct new container terminals. Simulations that support user needs require modeling tools that are both easy to use and sufficiently to reflect real world system. The object-oriented approach provides for both reusability and modularity that best fits these requirements. This paper present the design procedure a simulator for port container terminal that was based on the object-oriented approach. The simulator in order to model and simulate the TC-based container terminals is developed.

• 정보처리학회논문지B
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• 제8B권5호
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• pp.501-506
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• 2001

최근에 인터넷과 통신망의 활성화로 인하여 멀티미디어 정보들을 효율적으로 관리하고 서비스하기 위한 여러 가지 방법들의 제안되고 있다. 본 논문에서는 퍼지 기반의 멀티미디어 사서함 구축을 위한 객체관리기로서 $\alpha$-cut 을 이용한 FBOM을 제안한다. 제안된 시스템은 퍼지 필터링을 이용하여 객체들을 고나리하기 위해 객체 분류, 퍼지 필터링, 클래스 생성구조를 이용한다. 또한 제안된 시스템의 성능을 알아보기 위해 1000개의 멀티미디어 정보를 이용하여 실험을 수행하고, 랜덤 키 방법과 FBOM 방법을 비교 분석한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1121-1141
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• 2020

We propose a robust visual object tracking algorithm fusing a convolutional neural network tracker trained offline from a large number of video repositories and a color histogram based tracker to track objects for mixing immersive audio. Our algorithm addresses the problem of occlusion and large movements of the CNN based GOTURN generic object tracker. The key idea is the offline training of a binary classifier with the color histogram similarity values estimated via both trackers used in this method to opt appropriate tracker for target tracking and update both trackers with the predicted bounding box position of the target to continue tracking. Furthermore, a histogram similarity constraint is applied before updating the trackers to maximize the tracking accuracy. Finally, we compute the depth(z) of the target object by one of the prominent unsupervised monocular depth estimation algorithms to ensure the necessary 3D position of the tracked object to mix the immersive audio into that object. Our proposed algorithm demonstrates about 2% improved accuracy over the outperforming GOTURN algorithm in the existing VOT2014 tracking benchmark. Additionally, our tracker also works well to track multiple objects utilizing the concept of single object tracker but no demonstrations on any MOT benchmark.

• 한국컴퓨터산업학회논문지
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• 제8권2호
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• pp.89-96
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• 2007

객체기반 예약스케줄링 기법은 제약만족문제(CSP; Constraint Satisfaction Problem)와 객체지향개념(Object-Oriented Concepts)을 기반으로 승무원 객체들이 갖고 있는 사건들을 주어진 제약들에 만족하도록 목표인 운항스케줄 보드에 배정하는 기법이다. 본 논문에서는 객체기반 예약스케줄링기법을 항공운항 스케줄에 적용하여 승무원(운항승무원, 객실승무원)들의 운항 스케줄 만족도를 향상시키고, 승무원들에 대한 인력관리상의 문제점들을 해결하고자 하였다 특히, 승무원들의 운항스케줄에 대한 만족도를 향상시키기 위해서 전체승무원 선호도보드를 이용하였다. 승무원들의 스케줄 우선순위에 따라서 자원(타임 슬롯)을 배정하고, 자원에 대한 승무원들의 선호도 차이를 가질 수 있게 하였다. 보드에 대한 정의와 모든 사건들에 대한 정보를 전역제약으로 사용하고, 승무원들이 가지는 보드의 타임 슬롯들에 대한 선호도를 지역 제약으로 사용하였다. 또한 실제로 항공운항 스케줄링을 모의실험해서 승무원들의 운항 스케줄 만족도를 살펴보았다.

• 반도체디스플레이기술학회지
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• 제15권3호
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• pp.46-50
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• 2016

Recently, Depending on expectancy effect and ripple effect of augmented reality, the convergence between augmented reality and culture & arts are being actively conducted. This paper proposes a learning method for effective object tracking in 3D storytelling augmented reality in cultural properties. The proposed system is based on marker-less tracking, and there are four modules that are recognition, tracking, detecting and learning module. Recognition module is composed of SURF and LSH, and then this module generates standard object information. Tracking module tracks an object using object tracking based on reliability. This information is stored in Learning module along with learned time information. Detecting module finds out the object based on having the best possible knowledge available among the learned objects information, when the system fails to track. Also, it proposes a method for robustly implementing a 3D storytelling augmented reality in cultural properties in the future.

• 컴퓨터교육학회논문지
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• 제5권1호
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• pp.99-108
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• 2002

윈도우 프로그래밍과 인터넷 프로그래밍의 수요가 증대함에 따라 객체 지향 프로그래밍 언어에 대한 교육과 객체 지향 소프트웨어 개발에 관한 교육의 중요성이 높아가고 있다. 그러나, 새로운 분야의 개발 기법을 익힌다는 것은 쉬운 일이 아니다. 본 논문에서는 소프트웨어 재사용의 개념과 기법을 객체 모델링 교육에 접목하려고 노력하였다. 즉, 객체 모델링 단계에서 이전의 경험을 재사용할 수 있는 환경을 통해 객체 모델 구축 기법을 효과적으로 학습하도록 지원하고자 한다. 이를 위하여 학습과정에서 질의와 라이브러리에 저장된 컴포넌트에 대한 유사,일치성(Aanalogy)을 판단하여 라이브러리의 모델과 패턴을 재사용할 수 있는 방법을 제안하였다. 이로써 이미 잘 정의된 모델의 이해를 통해 교육 과정의 효과를 증대할 수 있을 것으로 기대한다. 또한 유추 기법(Analogy reasoning) 활용하므로써 단순한 키워드에 의한 재사용 라이브러리 검색 보다는 보다 폭넓은 범위의 대상 검색이 가능하도록 지원한다.