• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.4098-4116
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• 2020

Mobile devices such as smartphones are very attractive targets for augmented reality (AR) services, but their limited resources make it difficult to increase the number of objects to be recognized. When the recognition process is scaled to a large number of objects, it typically requires significant computation time and memory. Therefore, most large-scale mobile AR systems rely on a server to outsource recognition process to a high-performance PC, but this limits the scenarios available in the AR services. As a part of realizing large-scale standalone mobile AR, this paper presents a solution to the problem of accuracy, memory, and speed for large-scale object recognition. To this end, we design our own basic feature and realize spatial locality, selective feature extraction, rough pose estimation, and selective feature matching. Experiments are performed to verify the appropriateness of the proposed method for realizing large-scale standalone mobile AR in terms of efficiency and accuracy.

• Journal of information and communication convergence engineering
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• 제21권4호
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• pp.329-336
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• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• 한국자동차공학회논문집
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• 제14권3호
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• pp.58-67
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• 2006

In this paper, fuzzy logic based active ventilation system with security function is proposed and implemented. We can easily experience the situation that inner air is so hot to get start immediately after parking at summer day. Hot temperature is enough to explode a gas lighter or to suffocate a little chid. Proposed system has 1 blower and 2 axial fans to ventilate inner air. Based on the fuzzy logic, speed and direction of each fan are controlled. In addition to controlling fans, controller put down windows and adjust the periods of open time. In order to prevent the theft and security problems, IR sensors are used to detect objects. On detecting objects, controller put up windows. Experimental result shows that implemented system can be effectively ventilate inner air and reduce temperature. Proposed system can be applicable to commercial automobiles.

• 반도체디스플레이기술학회지
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• 제15권3호
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.414-419
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• 2006

The ballast or other objects may be located on the rail road by a lump of ice, repairing operation on the track, or the strong gust due to the high speed running of the train. When a train operated in this condition, it causes serious damages to the wheel, train, and structures near the track, or the secondary ballast flying. To remove these objects safely, a ballast blower is suggested which was attached under the train. Firstly, the numerical analyses are investigated to find out the basic flow characteristics of the ballast blower. Next, the performance of the ballast blower is verified by wind tunnel experiments. Through these studies, it is expected that the ballast blower can be applied practically.

• 한국정보처리학회논문지
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• 제6권10호
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• pp.2809-2815
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• 1999

Level set, and active contour(snakes) models are extensively used for image segmentation or shape extraction in computer vision. Snakes utilize the energy minimization concepts, and level set is based on the curve evolution in order to extract contours from image data. In general, these two models have their own drawbacks. For instance, snake acts pooly unless it is placed close to the wanted shape boundary, and it has difficult problem when image has multiple objects to be extracted. But, level set method is free of initial curve position problem, and has ability to handle topology of multiple objects. Nevertheless, level set method requires much more calculation time compared to snake model. In this paper, we use good points of two described models and also apply multi resolution algorithm in order to speed up the process without decreasing the performance of the shape extraction.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권3_4호
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• pp.285-292
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• 2003

기존에 개발된 MPEG-4 플레이어들을 살펴보면, 객체의 삽입, 삭제, 갱신과 같은 사용자 상호작용에 의한 시청각 장면 프리젠테이션시 전체 미디어 객체를 다시 프리젠테이션해야 하므로 화면이 껌뻑이거나 프리젠테이션 속도가 느렸다. 본 논문에서는 이를 개선하기 위해 객체 우선 순위 컴포지션 방법을 제안한다. 이는 복합 미디어 객체로 구성된 시청각 장면을 사용자 상호자용에 의해 실시간으로 객체가 삽입, 삭제, 갱신되는 장면 변화를 보다 효율적으로 프리젠테이션하는 방법이다. 제안된 방법으로 구현한 결과는 MPEG-4 스트림의 즉각적이고 자연스러운 프리젠테이션이 가능함을 보여준다

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• 한국콘텐츠학회논문지
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• 제19권9호
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• pp.666-673
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• 2019

몰입 가상현실 환경에서 사용자들은 다양한 가상객체들을 선택하여 목표로 하는 일을 수행할 수 있다. 사용자가 원하는 가상객체를 선택하기 위해서는 일반적으로 사용자의 시야에서 가상의 선분을 발사하여 그 선분과 객체가 일치되었을 때 객체를 선택하게 하는 Ray-Casting이나 여러 객체들을 동시에 선택해서 원하는 객체를 선택하는 Cone-Casting 기반의 객체선택 방법들이 널리 사용된다. 하지만 CAD에서 사용되는 가상객체들은 그 자체적으로 세부적인 작은 객체들로 구성되고 결합이 되어 있어서 사용자의 시야에서 원하는 객체를 기존 방법들로 선택하는 경우 사용자가 원하는 객체가 아니라 다른 객체가 선택되는 모호성 문제가 발생하여 원하는 객체를 선택하는데 문제가 발생하며, 그룹으로 객체를 선택하더라도 원하는 객체를 선택하기 위해서 결국 가상객체들의 위치 및 구조 등을 변경해야 하는 추가 작업을 해야 하는 문제가 발생한다. 본 논문에서는 가상객체가 여러 작은 세부적인 가상객체들로 구성이 되어 있더라도 이들이 가지고 있는 공간적인 연관 관계를 계산하고 이 연관 관계에 따라서 세부적인 가상객체들을 펼치거나 줄여서 사용자가 선택을 원하는 객체를 빠르고 정확하게 선택하는 방법을 제공한다. 본 논문에서는 본 논문에서 제안한 Adaptive-Casting 선택 방법과 기존의 Ray-Casting 과 Cone-Casting 방법들과 성능비교 실험을 하였다. 실험 결과 본 논문에서 제안한 방법이 사용자가 원하는 객체를 선택할 때 걸리는 속도가 가장 빠르면서 정확하다는 결과를 보여주었다.

• 제어로봇시스템학회논문지
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• 제14권6호
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• pp.519-522
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• 2008

As industry of a semiconductor and LCD industry have been rapidly growing, precision technologies of machining such as etching and 3D measurement are required. Stylus has been important measuring method in traditional manufacturing process. However, its disadvantages are low measuring speed and damage possibility at contacting point. To overcome mentioned disadvantage, non-contacting measurement method is needed such as PMP(Phase Measuring Profilometry), WSI(white scanning interferometer) and Confocal Profilometry. Among above 3 well-known methods, WSI started to be applied to FPD(flat panel display) manufacturing process. Even though it overcomes 21t ambiguity of PMP method and can measure objects which has specular surface, the measuring speed and vibration coming from manufacturing machine are one of main issue to apply full automatic total inspection. In this study, We develop high speed WSI system and algorithm to reduce unknown noise. The developing WSI and algorithm are implemented to measure 3D surface of wafer. Experimental results revealed that the proposed system and algorithm are able to measure 3D surface profile of wafer with a good precision and high speed.