• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.252-259
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• 2017

Nowadays, the existing manual method for recording actual progress of the construction site has some drawbacks, such as great reliance on the experience of professional engineers, work-intensive, time consuming and error prone. A method integrating computer vision and BIM(Building Information Modeling) is presented for indoor automatic progress monitoring. The developed method can accurately calculate the engineering quantity of target component in the time-lapse images. Firstly, sample images of on-site target are collected for training the classifier. After the construction images are identified by edge detection and classifier, a voting algorithm based on mathematical geometry and vector operation will divide the target contour. Then, according to the camera calibration principle, the image pixel coordinates are conversed into the real world Coordinate and the real coordinates would be corrected with the help of the geometric information in BIM model. Finally, the actual engineering quantity is calculated.

• 한국정보전자통신기술학회논문지
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• 제6권2호
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 한국정보전자통신기술학회논문지
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• 제7권1호
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• pp.61-67
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• 2014

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter(AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• 한국BIM학회 논문집
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• 제7권1호
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• pp.45-53
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• 2017

Continuous research efforts have been made on acquiring location data on construction sites. As a result, GPS and RFID are increasingly employed on the site to track the location of equipment and materials. However, these systems are based on radio frequency technologies which require attaching tags on every target entity. Implementing the systems incurs time and costs for attaching/detaching/managing the tags or sensors. For this reason, efforts are currently being made to track construction entities using only cameras. Vision-based 3D tracking has been presented in a previous research work in which the location of construction manpower, vehicle, and materials were successfully tracked. However, the proposed system is still in its infancy and yet to be implemented on practical applications for two reasons. First, it does not involve entity matching across two views, and thus cannot be used for tracking multiple entities, simultaneously. Second, the use of a checker board in the camera calibration process entails a focus-related problem when the baseline is long and the target entities are located far from the cameras. This paper proposes a vision-based method to track multiple workers simultaneously. An entity matching procedure is added to acquire the matching pairs of the same entities across two views which is necessary for tracking multiple entities. Also, the proposed method simplified the calibration process by avoiding the use of a checkerboard, making it more adequate to the realistic deployment on construction sites.

• 스마트미디어저널
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• 제1권2호
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• pp.12-22
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• 2012

최근 비디오 감시, 로봇 시각 휴대폰 등 무수히 많은 카메라가 생활 속에 파고들면서 휴먼 동작 인식은 컴퓨터 시각 분야의 새로운 붐을 일으키고 있다. 자체로 그다지 흥미 있는 동작은 아니지만 걸음걸이 또는 보행은 가장 보편적으로 많이 관찰되는, 의심할 여지없이 사람의 대표적인 동작이다. 그리 오래되지 않은 과거에 보행자 인식의 관점에서 반짝 연구가 있었지만 관심의 길이가 짧은 만큼 보행 동작에 관한 체계적인 분석과 이해 없이 이루어졌었다. 본 연구에서는 일련의 점진적인 모델을 이용하여 보행 동작의 구조를 체계적으로 분석하고자 한다. 입력 영상 신호의 다양한 변형과 불완전성을 극복할 수 있는 동적 베이스망 기반의 보행자 모델과 보행 모델을 제시한다. 그리고 이변량 폰 미제스 분포의 조건부 밀도 함수를 기반으로 마르코프 체인의 이산 상태 공간을 연속 공간으로 확장하는 방법을 제안한다. 제안된 모형화 프레임워크를 이용한 일련의 시험, 분석에서 보행자를 91.67% 인식하며 보행 동작을 보행 방향과 보행 자세의 두 가지 독립적인 성분으로 분리 해석할 수 있었다.

• 센서학회지
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• 제11권5호
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• pp.255-262
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• 2002

인간의 망막은 효율적으로 주어진 물체의 윤곽을 검출할 수 있다. 본 연구에서는 윤곽검출에 관여하는 망막 세포의 기능을 전자회로로 모델링하여 윤곽검출기능을 가지는 CMOS 시각칩을 설계하였다. CMOS 제조공정 중에는 여러 가지 요인에 의해 MOSFET의 특성이 변화할 수 있으며, 특히 어레이로 구성되어 각 픽셀의 신호를 출력하는 readout 회로에서의 특성변화는 출력옵셋으로 나타난다. 하드웨어로 입력영상의 윤곽을 검출하는 시각칩은 다른 응용시스템의 입력단에 사용되므로 이러한 옵셋은 전체 시스템의 성능을 결정하는 중요한 요소이다. 본 연구에서는 이와 같은 출력단의 옵셋을 제거하기 위해 CDS(Correlated Double Sampling) 회로를 이용한 윤곽 검출용 시각칩을 설계하였다. 설계된 시각칩은 CMOS 표준공정을 이용하여 다른 회로와 집적화가 가능하며, 기존의 시각칩보다 신뢰성 있는 출력특성을 나타냄으로써, 물체의 윤곽을 이용하는 물체추적, 지문인식, 인간 친화적 로봇시스템등의 다양한 응용 시스템의 입력단으로 적용될 수 있을 것이다.

• 제어로봇시스템학회논문지
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• 제22권3호
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• pp.210-216
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• 2016

This paper presents a novel collision avoidance technique for mobile robots based on omni-directional vision simultaneous localization and mapping (SLAM). This method estimates the avoidance path and speed of a robot from the location of an obstacle, which can be detected using the Lucas-Kanade Optical Flow in images obtained through fish-eye cameras mounted on the robots. The conventional methods suggest avoidance paths by constructing an arbitrary force field around the obstacle found in the complete map obtained through the SLAM. Robots can also avoid obstacles by using the speed command based on the robot modeling and curved movement path of the robot. The recent research has been improved by optimizing the algorithm for the actual robot. However, research related to a robot using omni-directional vision SLAM to acquire around information at once has been comparatively less studied. The robot with the proposed algorithm avoids obstacles according to the estimated avoidance path based on the map obtained through an omni-directional vision SLAM using a fisheye image, and returns to the original path. In particular, it avoids the obstacles with various speed and direction using acceleration components based on motion information obtained by analyzing around the obstacles. The experimental results confirm the reliability of an avoidance algorithm through comparison between position obtained by the proposed algorithm and the real position collected while avoiding the obstacles.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.920-927
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• 2009

Many schedule delays and cost overruns in interior construction are caused by a lack of understanding in detailed and complicated interior works. To minimize these potential impacts in interior construction, a systematic approach for project managers to detect discrepancies at early stages and take corrective action through use of visualized data is required. This systematic implementation is still challenging: monitoring is time-consuming due to the significant amount of as-built data that needs to be collected and evaluated; and current interior construction progress reports have visual limitations in providing spatial context and in representing the complexities of interior components. To overcome these issues, this research focuses on visualization and computer vision techniques representing interior construction progress with photographs. The as-planned 3D models and as-built photographs are visualized in a 3D walk-through model. Within such an environment, the as-built interior construction elements are detected through computer vision techniques to automatically extract the progress data linked with Building Information Modeling (BIM). This allows a comparison between the as-planned model and as-built elements to be used for the representation of interior construction progress by superimposing over a 3D environment. This paper presents the process of representing and detecting interior construction components and the results for an ongoing construction project. This paper discusses implementation and future potential enhancement of these techniques in construction.

• 전자공학회논문지SC
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• 제42권4호
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• pp.11-18
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• 2005

인간은 의사 표현을 위해 음성언어 뿐 아니라 몸짓 언어(body languages)를 많이 사용한다 이 몸짓 언어 중 대표적인 것은, 물론 손과 팔의 사용이다. 따라서 인간 팔의 운동 해석은 인간과 기계의 상호 작용(human-computer interaction)에 있어 매우 중요하다고 할 수 있다. 이러한 견지에서 본 논문에서는 다음과 같은 방법으로 컴퓨터비전을 이용한 인간팔의 3차원 자세 추정 방법을 제안하다. 먼저 팔의 운동이 대부분 회전 관절(revolute-joint)에 의해 이루어진다는 점에 착안하여, 컴퓨터 비전 시스템을 활용한 회전 관절의 3차원 운동 해석 기법을 제안한다. 이를 위해 회전 관절의 기구학적 모델링 기법(kinematic modeling techniques)과 컴퓨터 비전의 경사 투영 모델(perspective projection model)을 결합한다. 다음으로, 회전 관절의 3차원 운동해석 기법을 컴퓨터 비전을 이용한 인간 팔의 3차원 자세 추정 문제에 웅용한다. 그 기본 발상은 회전 관절의 3차원 운동 복원 알고리즘을 인간 팔의 각 관절에 순서 데로 적용하는 것이다. 본 알고리즘은 특히 유비쿼터스 컴퓨팅(ubiquitous computing)과 가상현실(virtual reality)를 위한 인간-컴퓨터 상호작용(human-computer interaction)이라는 응용을 목표로, 고수준의 정확도를 갖는 폐쇄구조 형태(closed-form)의 해를 구하는데 주력한다.

• 한국통신학회논문지
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• 제35권12C호
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• pp.984-994
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• 2010

Pose variation is a critical problem in face recognition. Three-dimensional(3D) face recognition techniques have been proposed, as 3D data contains depth information that may allow problems of pose variation to be handled more effectively than with 2D face recognition methods. This paper proposes a pose-normalized 3D face modeling method that translates and rotates any pose angle to a frontal pose using a plane fitting method by Singular Value Decomposition(SVD). First, we reconstruct 3D face data with stereo vision method. Second, nose peak point is estimated by depth information and then the angle of pose is estimated by a facial plane fitting algorithm using four facial features. Next, using the estimated pose angle, the 3D face is translated and rotated to a frontal pose. To demonstrate the effectiveness of the proposed method, we designed 2D and 3D face recognition experiments. The experimental results show that the performance of the normalized 3D face recognition method is superior to that of an un-normalized 3D face recognition method for overcoming the problems of pose variation.