• International conference on construction engineering and project management
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• 2013.01a
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• pp.616-623
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• 2013

One of the oldest, most common engineering problems is measuring the dimensions of different objects and the distances between locations. In AEC/FM, related uses vary from large-scale applications such as measuring distances between cities to small-scale applications such as measuring the depth of a crack or the width of a welded joint. Within the last few years, advances in applying new technologies have prompted the development of new measuring devices such as ultrasound and laser-based measurers. Because of wide varieties in type, associated costs, and levels of accuracy, the selection of an optimal measuring technology is challenging for construction engineers and facility managers. To tackle this issue, we present an overview of various measuring technologies adopted by experts in the area of AEC/FM. As the next step, to evaluate the performance of these technologies, we select one indoor and one outdoor case and measure several dimensions using six categories of technologies: tapes, total stations, laser measurers, ultrasound devices, laser scanners, and image-based technologies. Then we evaluate the results according to various metrics such as accuracy, ease of use, operation time, associated costs, compare these results, and recommend optimal technologies for specific applications. The results also revealed that in most applications, computer vision-based technologies outperform traditional devices in terms of ease of use, associated costs, and accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.26 no.1
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• pp.108-113
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• 2017

In this paper, we proposed a three-dimensional(3D) scanning system based on laser vision technique for 3D model reconstruction. The proposed scanning system consists of line laser, camera, and turntable. We implemented the 3D scanning system using low quality elements. Although these are low quality elements, we reduced the 3D data reconstruction errors greatly using two methods. First, we developed a maximum brightness detection algorithm. This algorithm extracts the maximum brightness of the line laser to obtain the shape of the object. Second, we designed a new laser control device. This device helps to adjust the relative position of the turntable and line laser. These two methods greatly reduce the measuring noise. As a result, point cloud data can be obtained without complicated calculations.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.67-72
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• 2002

A technique for alignment to true north is presented, based on synchronized measurements of vision image by a camera and output voltage of wind direction sensor. The true wind direction is evaluated by means of image processing techniques with least square sense, and then evaluated true value is compared with measured output voltage of the sensor. The proposed technique is applied to real meteorological tower m Daekwanryung test site. In addition, some uncertainty analysis of this method is presented.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1830-1835
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• 2015

In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.4
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• pp.249-254
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• 2013

In the area of computer vision, face recognition is being intensively researched. It is generally known that before a face is recognized it must be localized. Skin-color information is an important feature to segment skin-color regions. To extract skin-color regions the skin-color model based on multi-layer perceptron has been proposed. Extracted regions are analyzed to emphasize ellipsoidal regions. The results from this study show good accuracy for our vehicle driver face detection system.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.280-293
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• 2018

The conversion of an invisible thermal radiation pattern of an object into a visible image using infrared (IR) thermal technology is very useful to understand phenomena what we are interested in. Although IR thermal images were originally developed for military and space applications, they are currently employed to determine thermal properties and heat features in various applications, such as the non-destructive evaluation of industrial equipment, power plants, electricity, military or drive-assisted night vision, and medical applications to monitor heat generation or loss. Recently, IR imaging-based monitoring systems have been considered for application in agricultural, including crop care, plant-disease detection, bruise detection of fruits, and the evaluation of fruit maturity. This paper reviews recent progress in the development of IR thermal imaging techniques and suggests possible applications of thermal imaging techniques in agriculture.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2870-2872
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• 2005

본 논문에서는 시각기반 센서 네트워크에 의해 다중물체의 위치를 인식 및 추적하여 목표물들의 위치를 결정할 수 있는 분산형 시각 시스템을 제시한다. 각 시각 센서는 칼라와 동작 정보에 의한 대상물체의 정확한 분할 및 다중물체에 대한 실시간 추적 그리고 간단한 원근법에 의한 포즈 추정을 수행한다. 각 시각 센서를 하나의 에이전트 - 시각 에이전트 -로 정의하고, 전체 시각기반 센서 네트워크를 복수 에이전트 시스템(multiagent system)으로 구성한다. 이로써 대상물체의 핸드오버시 그 대상물체의 신분에 대한 매칭 문제를 Identified Contract Net (ICN) 프로토콜을 제안하여 해결한다. ICN 프로토콜은 시각 에이전트의 개수에 독립적이고 그것을 사용할 경우 시각 에이전트들 간의 캘리브레이션도 필요로 하지 않기 때문에 시각기반 센서 네트워크의 속도, 확장성 및 모듈성을 높여준다. 실험을 통해 구성한 시각기반 센서 네트워크에서 ICN 프로토콜이 적용됨을 성공적으로 검증하였다.

• Journal of Information Processing Systems
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• v.5 no.2
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• pp.41-68
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• 2009

Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Face recognition techniques can be broadly divided into three categories based on the face data acquisition methodology: methods that operate on intensity images; those that deal with video sequences; and those that require other sensory data such as 3D information or infra-red imagery. In this paper, an overview of some of the well-known methods in each of these categories is provided and some of the benefits and drawbacks of the schemes mentioned therein are examined. Furthermore, a discussion outlining the incentive for using face recognition, the applications of this technology, and some of the difficulties plaguing current systems with regard to this task has also been provided. This paper also mentions some of the most recent algorithms developed for this purpose and attempts to give an idea of the state of the art of face recognition technology.