• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.174-184
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• 2022

3D human pose estimation models can be classified into a multi-view model and a single-view model. In general, the multi-view model shows superior pose estimation performance compared to the single-view model. In the case of the single-view model, the improvement of the 3D pose estimation performance requires a large amount of training data. However, it is not easy to obtain annotations for training 3D pose estimation models. To address this problem, we propose a method to generate pseudo ground-truths of multi-view human pose data from a multi-view model and exploit the resultant pseudo ground-truths to train a single-view model. In addition, we propose a multi-view consistency loss function that considers the consistency of poses estimated from multi-view images, showing that the proposed loss helps the effective training of single-view models. Experiments using Human3.6M and MPI-INF-3DHP datasets show that the proposed method is effective for training single-view 3D human pose estimation models.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.41-46
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• 2022

This study analyzed the results and implications of the industry-university cooperation human resource nurturing process based on the I-O model for the Motion Graphics major and the Global Hotelier major in Baek seok University. In this study, based on the analysis of the human resources training performance through industry-university cooperation in the motion graphics and hotelier fields for 5 years, what kind of efforts were made for successful human resource training, and the level of performance was analyzed and improvement points were suggested. In this study, four strategies were set for successful industry-university-tailored human resource nurturing: student-industry matching through industry participation in education, industry-university integrated education, education quality advancement, and customized education infrastructure construction. As a result of the analysis, customized human resource training should first be developed through industry demand survey and a mirror-type practice room should be built to fit the corporate environment. Second, it was found that it is possible to be individual only if there is an active participation of industry experts throughout the curriculum such as subjects and non-subjects.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.517-524
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• 2022

Human pose estimation is a method of estimating a posture by extracting a human joint key point. When occlusion occurs, the joint key point extraction performance is lowered because the human joint is covered. The occlusion phenomenon is largely divided into three types of actions: self-contained, covered by other objects, and covered by background. In this paper, we propose an effective posture estimation method using a masking phenomenon enhancement technique. Although the posture estimation method has been continuously studied, research on the occlusion phenomenon of the posture estimation method is relatively insufficient. To solve this problem, the author proposes a data augmentation technique that intentionally masks human joints. The experimental results in this paper show that the intentional use of the blocking phenomenon enhancement technique is strong against the blocking phenomenon and the performance is increased.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1808-1813
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• 2004

Recognition of human motions using their 2-D images has various applications. An eigenspace method is employed in this paper for representing and recognizing human motions. An eigenspace is created from the images taken by multiple cameras that surround a human in motion. Image streams obtained from the cameras compose the same number of curved lines in the eigenspace and they are used for recognizing a human motion in a video image. Performance of the proposed technique is shown experimentally.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1506-1511
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• 2018

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, Linear Prediction(LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is used for indicating the degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that the proposed scheme achieved good performances for evaluation of human sensibility.

• ETRI Journal
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• v.35 no.6
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• pp.949-959
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• 2013

Since the recent launch of Microsoft Xbox Kinect, research on 3D human pose estimation has attracted a lot of attention in the computer vision community. Kinect shows impressive estimation accuracy and real-time performance on massive graphics processing unit hardware. In this paper, we focus on further reducing the computation complexity of the existing state-of-the-art method to make the real-time 3D human pose estimation functionality applicable to devices with lower computing power. As a result, we propose two simple approaches to speed up the random-forest-based human pose estimation method. In the original algorithm, the random forest classifier is applied to all pixels of the segmented human depth image. We first use a multi-scale approach to reduce the number of such calculations. Second, the complexity of the random forest classification itself is decreased by the proposed cascade approach. Experiment results for real data show that our method is effective and works in real time (30 fps) without any parallelization efforts.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.2048-2051
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• 2010

Almost all companies have paid much attention to the safety management ranging from maintenance to operation even at the stage of designing in order to prevent accidents, but fatal accidents continue to increase throughout the world. In particular, it is essential to systematically prevent such fatal accidents as fire, explosion or leakage of toxic gas at factories in order to not only protect the workers and neighbors but also prevent economic losses and environmental pollution. In addition, HRA may be used to detect the human errors which may cause accidents or trace back to any mistake on the part of workers. Usually, HRA technique is used in association with other risk assessment techniques. Moreover, it can serve to enumerate the human errors which may occur during operation or down-time or correct the existing system to reduce the mistakes. This work focuses on the coincidence of human error and mechanical failure for management of human error, and on some important performance shaping factors to propose a method for improving safety effectively of the process industries.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.992-999
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• 2011

This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

• International Journal of Reliability and Applications
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• v.11 no.2
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• pp.123-138
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• 2010

This paper investigates a mathematical model of a system composed of two non-identical unit parallel system with common-cause failure, critical human error, non-critical human error, preventive maintenance and two type of repair, i.e. cheaper and costlier. This system goes for preventive maintenance at random epochs. We assume that the failure, repair and maintenance times are independent random variables. The failure rates, repair rates and preventive maintenance rate are constant for each unit. The system is analyzed by using the graphical evaluation and review technique (GERT) to obtain various related measures and we study the effect of the preventive maintenance preventive maintenance on the system performance. Certain important results have been derived as special cases. The plots for the mean time to system failure and the steady-state availability A(${\infty}$) of the system are drawn for different parametric values.

• Journal of the Ergonomics Society of Korea
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• v.20 no.2
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• pp.1-28
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• 2001

This paper deals with the selection of the important Influencing Factors (IFs) under accident management situations in nuclear power plants for use in the assessment of human errors. In order to achieve this goal, we collected two types of IF taxonomies, one is the full set IF list mainly developed for human error analysis. and the other is the IFs for human reliability analysis (HRA) in probabilistic safety assessment (PSA). Five sets of IF taxonomy among the full set IF list and ten sets of IF taxonomy among HRA methodologies were collected in the study. From the review and analysis of BRA IFs, we could obtain some insights for the selection of HRA IFs. By considering the situational characteristics of the accident management domain, candidate IFs are chosen. Finally, those IFs are structured hierarchically to be appropriate for the use in the assessment of human error under accident management situation. Three nuclear accidents such as TMI. Chernobyl and JCO were analysed to validate the proposed taxonomy.