• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.63.1-63
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• 2001

At 3-D vision measuring, the camera calibration is necessary to calculate parameters accurately. Camera calibration was developed widely in two categories. One is that establishes reference points in space, and the other is that uses the grid type frame and statistical method. But, the former has difficult to setup reference points and the latter has low accuracy. In this paper we present an algorithm for camera calibration using perspective ratio of the grid type frame with different line widths. The advantage of this algorithm is that it can estimate position, pose and distance between camera and object ...

• 대한원격탐사학회지
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• 제23권6호
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• pp.553-558
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• 2007

영상의 두점과 카메라 초점을 지나는 벡터들간의 사잇각을 기반한 방정식은 카메라 위치와 제세가 독립적으로 분리시킬 수 있다. 본 논문은 이 방정식의 두번째 응용으로써, 벡터내적 기반 방정식에 의해 생성된 곡면 분석을 통한 카메라와 레이져 라인 스캐너간의 상대적인 외부표정 계산을 소개한다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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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.

• 로봇학회논문지
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• 제3권1호
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.171-177
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• 2021

It is difficult to accurately extract features of pedestrian because the pedestrian is photographed at a crosswalk using a camera positioned higher than the pedestrian. In addition, it is more difficult to extract features when a part of the pedestrian's body is covered by an umbrella or parasol or when the pedestrian is holding an object. Representative methods to solve this problem include Object Detection, Instance Segmentation, and Pose Estimation. Among them, this study intends to use the Pose Estimation method. In particular, we intend to increase the recognition rate of pedestrians in crosswalks by maintaining the image resolution through HigherHRNet and applying the foot estimation technique. Finally, we show the superiority of the proposed method by applying and analyzing several data sets covered by body parts to the existing method and the proposed method.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.115-118
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• 2003

This paper describes a system of detecting multi-views faces and estimating their face poses in an omni-directional camera environment for non-intrusive iris recognition. The paper is divided into two parts; First, moving region is identified by using difference-image information. Then this region is analyzed with face-color information to find the face candidate region. Second part is applying PCA (Principal Component Analysis) to detect multi-view faces, to estimate face pose.

• 스마트미디어저널
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• 제13권1호
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• pp.24-35
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• 2024

The combination of Artificial Intelligence and the Internet of Things (AIoT) has gained significant popularity. Deep neural networks (DNNs) have demonstrated remarkable success in various applications. However, deploying complex AI models on embedded boards can pose challenges due to computational limitations and model complexity. This paper presents an AIoT-based system for smart parking lots using edge devices. Our approach involves developing a detection model and a decision tree for occupancy status classification. Specifically, we utilize YOLOv5 for car license plate (LP) detection by verifying the position of the license plate within the parking space.

• 한국멀티미디어학회논문지
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• 제21권10호
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• pp.1162-1170
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• 2018

This paper presents an augmented reality system for multiple users. The proposed system performs ar image-based pose estimation of users and pose of each user is shared with other uses via a network server. For camera-based pose estimation, we install multiple markers in a pre-determined space and select the marker with the best appearance. The marker is detected by corner point detection and for robust pose estimation. the marker's corner points are tracked by optical flow tracking algorithm. Experimental results show that the proposed system successfully provides an augmented reality application to multiple users even when users are rapidly moving and some of markers are occluded by users.

• Journal of Computing Science and Engineering
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• 제10권3호
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• pp.95-101
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• 2016

In this study, we propose a new system for constructing parallel corpora for sign languages, which are generally under-resourced in comparison to spoken languages. In order to achieve scalability and accessibility regarding data collection and corpus construction, our system utilizes deep learning-based techniques and predicts depth information to perform pose estimation on hand information obtainable from video recordings by a single RGB camera. These estimated poses are then transcribed into expressions in SignWriting. We evaluate the accuracy of hand tracking and hand pose estimation modules of our system quantitatively, using the American Sign Language Image Dataset and the American Sign Language Lexicon Video Dataset. The evaluation results show that our transcription system has a high potential to be successfully employed in constructing a sizable sign language corpus using various types of video resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권11호
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• pp.4103-4117
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• 2014

Image processing and computer vision algorithms are gaining larger concern in a variety of application areas such as robotics and man-machine interaction. Vision allows the development of flexible, intelligent, and less intrusive approaches than most of the other sensor systems. In this work, we determine the location and orientation of a mobile robot which is crucial for performing its tasks. In order to be able to operate in real time there is a need to speed up different vision routines. Therefore, we present and evaluate a method for introducing parallelism into the multiple non-overlapping camera pose estimation algorithm proposed in [1]. In this algorithm the problem has been solved in real time using multiple non-overlapping cameras and the Extended Kalman Filter (EKF). Four cameras arranged in two back-to-back pairs are put on the platform of a moving robot. An important benefit of using multiple cameras for robot pose estimation is the capability of resolving vision uncertainties such as the bas-relief ambiguity. The proposed method is based on algorithmic skeletons for low, medium and high levels of parallelization. The analysis shows that the use of a multiprocessor system enhances the system performance by about 87%. In addition, the proposed design is scalable, which is necaccery in this application where the number of features changes repeatedly.