• Advances in robotics research
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• v.2 no.2
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• pp.129-140
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• 2018

With the increasing demand for the development of human pose estimation, such as human-computer interaction and human activity recognition, there have been numerous approaches to detect the 2D poses of people in images more efficiently. Despite many years of human pose estimation research, the estimation of human poses with images remains difficult to produce satisfactory results. In this study, we propose a robust 2D human body pose estimation method using an RGB camera sensor. Our pose estimation method is efficient and cost-effective since the use of RGB camera sensor is economically beneficial compared to more commonly used high-priced sensors. For the estimation of upper-body joint positions, semantic segmentation with a fully convolutional network was exploited. From acquired RGB images, joint heatmaps accurately estimate the coordinates of the location of each joint. The network architecture was designed to learn and detect the locations of joints via the sequential prediction processing method. Our proposed method was tested and validated for efficient estimation of the human upper-body pose. The obtained results reveal the potential of a simple RGB camera sensor for human pose estimation applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6C
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• pp.623-628
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• 2006

This paper addresses the frequency offset estimation problem in the presence of the timing error for OFDM systems. When the timing error exists, the correlation value used for the frequency offset estimation could be reduced significantly due to the timing error, resulting in considerable degradation in estimation performance. In this paper, using the coherence phase bandwidth (CPB) and a threshold, a novel frequency offset estimation scheme is proposed and based on which, an efficient timing error estimation scheme is also proposed for the re-estimation of the frequency offset. The performance comparison results show that the proposed frequency offset estimation scheme is not only more robust to the timing error but also has less computational complexity, as compared with the conventional schemes. It is also demonstrated by simulation that theproposed timing error estimation scheme gives a reliable estimate of the timing error.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.106-108
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• 2009

In this paper, we handle automatic estimation of mechanical parameters for mobile robots. Most estimation methods are based on the sequence and move-measurement-estimation. Estimated accuracy is largely dependent on the paths. Mathematical conditions minimizing estimation errors are derived, and then a method finding optimal paths for mechanical parameters estimation is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.159.1-159
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• 2001

A new time-domain FIR parameter estimation called the receding horizon least square estimation (RHLSE) is suggested for stochastic systems by combining the well known least square estimation with the receding horizon strategy. It can be always obtained without the requirement of any \textit{a priori} information about the horizon initial parameter. A fast algorithm for the suggested estimation is also presented which is remarkable in the view of computational advantage and simple implementation. It is shown that the proposed estimation is robust against temporary modeling uncertainties due to their FIR structure through simulation studies.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.57-70
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• 2001

In this paper we consider a various estimation methods including the post-stratification estimation, regression estimation and calibration estimation or a generalized raking estimation under a unit nonresponse. All of them have a common type of calibration estimation based on the post-stratification for a categorical auxiliary variables.

• ETRI Journal
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• v.36 no.3
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• pp.460-468
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• 2014

This paper addresses the problem of joint time of arrival (TOA) and direction of arrival (DOA) estimation in impulse radio ultra-wideband systems with a two-antenna receiver and links the joint estimation of TOA and DOA to the sparse representation framework. Exploiting this link, an orthogonal matching pursuit algorithm is used for TOA estimation in the two antennas, and then the DOA parameters are estimated via the difference in the TOAs between the two antennas. The proposed algorithm can work well with a single measurement vector and can pair TOA and DOA parameters. Furthermore, it has better parameter-estimation performance than traditional propagator methods, such as, estimation of signal parameters via rotational invariance techniques algorithms matrix pencil algorithms, and other new joint-estimation schemes, with one single snapshot. The simulation results verify the usefulness of the proposed algorithm.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1810-1817
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• 2000

The purpose of this research is to develop an estimation model for information systems operating costs. Current cost estimation practices and types of sytem management projects have been reviewed an analyses. Typical operating project types of information systems are determined. They are application system operation, help disk operation, network management and operation, and hardware management. For each type of projects, cost factors ar identified and a structure of cost estimation model is defined. Cost estimation models have been constructed and tested by 24 real operation projects data. Statistical analysis shows derived models are statistically significant. User groups' opinion on these draft cost estimation model has been surveyed and summarized. The results of this research can be used as a cornerstone for future research on operating cost estimation, and for cost estimation guideline of information systems operation projects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2538-2541
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• 2005

This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

• Proceedings of the KIEE Conference
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• 2000.11a
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• pp.58-60
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• 2000

In this paper we present an estimation method of electric energy[kWh] for load management of pole-transformer. For the electric energy estimation, we use the nonlinear load research based estimation(NLRE) algorithm. The NLRE curve is the normalized annual cumulative energy consumption for a particular day in a year. And, it is used for the coefficient estimation. Estimation method of suggested electric energy of pole-transformer used billing cycle electric energy estimation equation is verified as comparison billing cycle electric energy and estimated electric energy. We can reduce the error of peak load estimation by suggested method than the conventional method in domestic.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.408-412
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• 2009

In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.