• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.916-924
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• 2014

It is possible to improve the accuracy of the motion estimation for a video by applying a variable block size. However, it has limits in the zoom motion estimation. In this paper, we propose a method for estimating the zoom motion with variable block size. The proposed method separates the background within the object picture by depth information obtained from a depth camera, and only the object regions are applied to zoom scale, but the background is not applied. In addition, the object regions select efficiently variable block size mode in consideration of the generated motion vectors and the accuracy of motion estimation at the same time. Simulation results show the accuracy of the motion estimation and the number of motion vectors for the proposed method. It is verified that the proposed method can reduce the number of motion while maintaining the similar accuracy of motion estimation than the conventional motion estimation methods.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.32-40
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• 2019

Indoor location estimation studies are needed in various fields. The method of estimating the indoor position can be divided into a method using hardware and a method using no hardware. The use of hardware is more accurate, but has the disadvantage of hardware installation costs. Conversely, the non-hardware method is not costly, but it is less accurate. To estimate the location for AR game, you need to get the solution of the Perspective-N-Point (PnP). To obtain the PnP problem, we need three-dimensional coordinates of the space in which we want to estimate the position and images taken in that space. The position can be estimated through six pairs of two-dimensional coordinates matching the three-dimensional coordinates. To further increase the accuracy of the solution, we proposed the use of an additional non-coplanarity degree to determine which points would increase accuracy. As the non-coplanarity degree increases, the accuracy of the position estimation becomes higher. The advantage of the proposed method is that it can be applied to all existing location estimation methods and that it has higher accuracy than hardware estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10B
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• pp.1813-1820
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• 2000

In this paper we proposed an efficient multiresolution motion estimation(MRME) algorithm using half-pixel accuracy motion estimation (HPAME) and characteristics of motion vectors in the baseband. Conventional MRME method needs exact motion vectors in the baseband because those are used as initial motion vectors in higher frequency subbands. Therefore the proposed method uses HPAME to estimate the motion vectors exactly in the baseband. Based on the characteristics of these motion vectors the motion vectors in the higher frequency subbands are selectively estimatied. That is motion vectors in the higher frequency subbands are estimated only for the blocks which have the half-pixel accuracy motion vectors in the baseband. In the proposed method by using HPAME in the baseband and selective motion estimation in the higher frequency subbands we can obtain reconstructed image with the similar quality with the conventional method though we reduce the computational complexity and the bit rate considerably.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.77-86
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• 1989

A fully automated cost estimation system(FACES) has been developed. Since speed, accuracy, and consistency are essential factors in automating a cost estimation, the use of computers in cost estimation system(CES) has grown rapidly in the last few years. FACES is a micro computer based cost estimation system that employs a manufacturing knowledge base. A Group Technology(GT) based part classification and coding(C&C) scheme is used to automate the process planning aspects of cost estimation. Variant process planning methods are employed to generate workstation routings from form features of the part. The system has been tested for an assembly of six machined parts. Results indicate that the system could provide a substantial improvement in accuracy, productivity, and performance over the more traditional full dialog approach to cost estimation. It also provides a good foundation for a factory automation by using a common GT based database through design to production.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1842-1848
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• 2017

Recently, user motion estimation methods using various wearable devices have been actively studied. In this paper, we propose a motion estimation system using Myo, which is one of the wearable devices, using two Myo and their dependency relations. The estimated motion is used as a command for remotely controlling the robot. Myo's Orientation and EMG signals are used for motion estimation. These two type data sets are used complementarily to increase the accuracy of motion estimation. We design and implement the system according to the proposed method and analyze the results through experiments. As a result of comparison with previous studies, the accuracy of motion estimation can be improved by about 12.3%.

• Journal of The Korean Association For Science Education
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• v.21 no.1
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• pp.76-88
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• 2001

This study explored people's accuracy and methods of estimating some base physical quantities, i.e. length, mass, time and temperature. A total of 40 members, ranging from freshmen to professors, of a physics education department of a local university were asked to make two different kinds of estimations, intuitive and operational, on two sets of objects. For intuitive estimation, they were asked to make estimations on four given objects (length - wood chopsticks, mass - rubber eraser, time electric fan, temperature - water in a cup) as soon as they faced with the objects, usually within a few seconds of seeing. For operational estimation, they were allowed to make estimations on a different set of objects (length - plastic rod, mass - lock, time - simple pendulum, temperature - water in a cup) with enough time and they could apply various available methods (e.g. using pencil to estimate the object's length, counting their own pulse rate to estimate time) for the estimation. The findings of this study can be summarized as follows: (1) for length, mass and temperature the intuitive estimations were better performed while for the time estimation the result was the reverse; (2) there was no positive relationship between the amount of physics experience and the accuracy of the estimation; (3) in general, people's accuracy of the length estimation was best performed while their mass estimation was worst performed; (4) people used their own various methods for estimation, esp. using nearby objects around them and applying mental units which have convenient values (e.g. 30cm, 50cm, 1kg, 1 Keun, 1 second).

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1721-1726
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• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.119-133
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• 2009

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.315-327
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• 2004

Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.