• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.762-770
• /
• 2014

Tangible Space Initiative (TSI) is a new framework that can provide a more natural and intuitive Human Computer Interface for users. This is composed of three cooperative components: a Tangible Interface, Responsive Cyber Space, and Tangible Agent. In this paper we present a Tangible Tele-Meeting system in TSI, which allows people to communicate with each other without any spatial limitation. In addition, we introduce a method for registering a Tangible Avatar with a Tangible Agent. The suggested method is based on relative pose estimation between the user and the Tangible Agent. Experimental results show that the user can experience an interaction environment that is more natural and intelligent than that provided by conventional tele-meeting systems.

• Journal of Biomedical Engineering Research
• /
• v.39 no.6
• /
• pp.278-283
• /
• 2018

Nowdays, many people suffer from the neck pain due to forward head posture(FHP) and text neck(TN). To assess the severity of the FHP and TN the craniovertebral angle(CVA) is used in clinincs. However, it is difficult to monitor the neck posture using the CVA in daily life. We propose a new method using the cervical flexion angle(CFA) obtained from a wearable sensor to monitor neck posture in daily life. 15 participants were requested to pose FHP and TN. The CFA from the wearable sensor was compared with the CVA observed from a 3D motion camera system to analyze their correlation. The determination coefficients between CFA and CVA were 0.80 in TN and 0.57 in FHP, and 0.69 in TN and FHP. From the monitoring the neck posture while using laptop computer for 20 minutes, this wearable sensor can estimate the CVA with the mean squared error of 2.1 degree.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.06a
• /
• pp.105-106
• /
• 2018

본 논문에서는 동적 프로젝션 맵핑을 구현하기 위하여 3차원 공간의 깊이 정보와 대상 객체의 색상영상에서의 특징점을 추출하여 3차원 공간상에서 움직이는 2차원 평면 객체의 자세를 안정적으로 추정하는 기법을 제안한다. 제안 기법은 타겟 이미지를 출력하여 타겟 이미지 보다 큰 평면 패널에 부착하고, 이 평면 패널을 3차원 공간상에서 움직이는 환경에서 타겟 이미지의 자세를 안정적으로 추정하기 위하여 고안되었다. 제안 기법에서는 우선 패널이 움직일 수 있는 깊이 영역을 지정하여 해당 깊이 영역에 존재하는 2차원 패널을 추출하고, 패널의 사각영역을 추출한다. 또한, 색상 영상에 SURF 알고리즘을 적용하여 2차원 평면상에 부착된 타겟 이미지의 영역을 색상 특징을 기반으로 함께 추출하여 패널의 사각 영역과 타겟 이미지의 상대적인 위치 정보를 추출한다. 셋업 단계에서 추출된 타겟 이미지의 상대적인 위치 정보를 이용하여, 조명의 변화에 의하여 순간적으로 타겟 이미지의 특징점 추적에 실패한 경우, 패널의 사각 영역에 의해 계산된 타겟 이미지의 상대적 위치 정보를 계산하여 자세 추정에 사용함으로써 움직이는 타겟 이미지의 3차원 자세를 안정적으로 추정할 수 있도록 하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.6
• /
• pp.143-148
• /
• 2022

It is very important for metaverse, mobile robot, and user location services to analyze the images continuously taken using a mobile smartphone or robot's monocular camera to estimate the camera's location. So far, PnP-related techniques have been applied to calculate the position. In this paper, the camera's moving direction is obtained using the essential matrix in the epipolar geometry applied to successive images, and the camera's continuous moving position is calculated through geometrical equations. A new estimation method was proposed, and its accuracy was verified through simulation. This method is completely different from the existing method and has a feature that it can be applied even if there is only one or more matching feature points in two or more images.

• Journal of Korea Multimedia Society
• /
• v.25 no.10
• /
• pp.1535-1545
• /
• 2022

Sign language has completely different meaning depending on the direction of the hand or the change of facial expression even with the same gesture. In this respect, it is crucial to capture the spatial-temporal structure information of each movement. However, sign language translation studies based on Sign2Gloss2Text only convey comprehensive spatial-temporal information about the entire sign language movement. Consequently, detailed information (facial expression, gestures, and etc.) of each movement that is important for sign language translation is not emphasized. Accordingly, in this paper, we propose Spatial-temporal Keypoints Centered Sign2Gloss2Text Translation, named STKC-Sign2 Gloss2Text, to supplement the sequential and semantic information of keypoints which are the core of recognizing and translating sign language. STKC-Sign2Gloss2Text consists of two steps, Spatial Keypoints Embedding, which extracts 121 major keypoints from each image, and Temporal Keypoints Embedding, which emphasizes sequential information using Bi-GRU for extracted keypoints of sign language. The proposed model outperformed all Bilingual Evaluation Understudy(BLEU) scores in Development(DEV) and Testing(TEST) than Sign2Gloss2Text as the baseline, and in particular, it proved the effectiveness of the proposed methodology by achieving 23.19, an improvement of 1.87 based on TEST BLEU-4.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.5
• /
• pp.61-68
• /
• 2021

In this paper, we propose an edge computing-based exercise data collection device that can be provided for exercise rehabilitation services. In the existing cloud computing method, when the number of users increases, the throughput of the data center increases, causing a lot of delay. In this paper, we design and implement a device that measures and estimates the position of keypoints of body joints for movement information collected by a 3D camera from the user's side using edge computing and transmits them to the server. This can build a seamless information collection environment without load on the cloud system. The results of this study can be utilized in a personalized rehabilitation exercise coaching system through IoT and edge computing technologies for various users who want exercise rehabilitation.

• Journal of Broadcast Engineering
• /
• v.27 no.4
• /
• pp.519-526
• /
• 2022

Identifying and searching for characters appearing in scenes during multimedia video editing is an arduous and time-consuming process. Applying artificial intelligence to labor-intensive media editing tasks can greatly reduce media production time, improving the creative process efficiency. In this paper, a method is proposed which combines existing artificial intelligence based techniques to automate character recognition and search tasks for video editing. Object detection, face detection, and pose estimation are used for character localization and face recognition and color space analysis are used to extract unique representation information.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.04a
• /
• pp.395-398
• /
• 2009

3 차원 객체 검색 및 자세 추정 기법은 의료, 보안 등의 다양한 산업 영역에서 매우 중요한 이슈 중 하나로써 연구되고 있다. 정확한 객체 검색 및 자세 추정을 위해서는 객체의 가능한 모든 영상 정보를 사용하여야 하기 때문에 많은 연산시간이 걸리게 되고, 특히 객체의 정확한 자세를 추정하기 위해서는 높은 CPU 의 성능과 큰 메모리 공간을 필요로 한다. 이러한 제약으로 인해, 3 차원 객체 검색 및 자세 추정은 상대적으로 하드웨어의 성능이 낮은 모바일 장치에서 실행되기 어려웠다. 따라서, 본 논문에서는 모바일 장치에서도 효과적으로 객체 검색 및 자세 추정이 가능하도록 하기 위한 클라이언트-서버 환경에서의 객체의 외형 기반 인덱스 구축 및 검색 기법을 제안한다. 제안된 기법의 주요 특징은 i) 모바일 장치의 하드웨어 환경을 고려하여 비교적 적은 수의 객체의 영상을 바탕으로 한 객체 검색 및 후보 자세 예측과 ii) 모바일 장치에서의 검색 결과와 많은 수의 객체 영상을 기반으로 한 서버에서의 정확한 자세 추정이다. 실험 결과에서는 제안된 기법들을 통해, 빠른 시간 내에 정확한 객체 검색 및 자세 추정이 가능함을 보였다.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.613-618
• /
• 2023

In this paper, a monitoring program that can automatically determine whether a patient admitted to an isolation room acts out of a stable state through a screen photographed in real time is described. The motion recognition model of this program was built by learning through transfer learning. 900 images were used for the three movements, and this program was developed for the web to support all environments. The model was determined with high accuracy to determine the state of the subject hospitalized in the isolation room, and can be applied by applying it to the existing isolation room monitoring system.

• The Journal of Korea Robotics Society
• /
• v.18 no.1
• /
• pp.72-81
• /
• 2023

We introduce tightly-coupled GNSS-LiDAR-Inertial state estimator, which is capable of SLAM (Simultaneously Localization and Mapping) and autonomous driving. Long term drift is one of the main sources of estimation error, and some LiDAR SLAM framework utilize loop closure to overcome this error. However, when loop closing event happens, one's current state could change abruptly and pose some safety issues on drivers. Directly utilizing GNSS (Global Navigation Satellite System) positioning information could help alleviating this problem, but accurate information is not always available and inaccurate vertical positioning issues still exist. We thus propose our method which tightly couples raw GNSS measurements into LiDAR-Inertial SLAM framework which can handle satellite positioning information regardless of its uncertainty. Also, with NLOS (Non-light-of-sight) satellite signal handling, we can estimate our states more smoothly and accurately. With several autonomous driving tests on AGV (Autonomous Ground Vehicle), we verified that our method can be applied to real-world problem.