• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.205-212
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• 2019

Motion tracking and localization devices are an important building block of motion tracking systems in a virtual reality (VR) environment. This study is about improving the accuracy of motion and location for enhancing user immersion in experience type VR environment to position tracking technique. In this study, we propose and test a design of such a device. The module data test of the attitude and heading reference system shows that the implementation with the MPU-9250 sensor is successful and adequate to be used with short operation time. We consider various sensor hardware dependencies of VR, and compare various correction methods and filtering methods to lower the motion to photon (MTP) time that user movement is fully reflected on the display using sensor devices. The Kalman filter is used to combine the accelerometer with the gyroscope in the sensing unit.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.137-140
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• 2021

High dynamic range (HDR) technology has been drawing attention in the field of imaging and consumer entertainment. As tools for capturing and creating HDR contents, encoding, and transmission evolve to support HDR formats, various display capabilities are being developed and increased. Hence, there is need for remapping native HDR imagery for display on lower quality legacy standard dynamic range (SDR) displays. This operation is referred to as tone mapping. In this paper, we present a sectional tone mapping method by Lenzen, and expand upon a tone mapping approach to improve temporal stability while maintaining picture quality. Compared to the existing block-based sectional tone mapping, our method uses the edge awareness-based tone mapping. We estimate the performance of the objective metric on temporal flickering. The experimental result shows that the algorithm maintains a smoother relationship between the output luminance values, and this reveals success in reducing halos and improving temporal stability with adopted edge aware filtering.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.886-887
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• 2023

This paper is about the development of kiosks that provide four types of service. Simple UI and educational videos solve the complexity of existing kiosks and provide an intuitive and convenient screen to users. In addition, the AR function, which is a three-dimensional form, shows directions and store representative images. After storing user information in the DB, a learning model is generated using user-based KNN collaborative filtering to provide a recommendation menu. As a result, it is possible to increase user convenience through kiosks using metaverse and AI recommendation services. It is also expected to solve digital alienation of social classes who have difficulty using kiosks.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.254-266
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• 2020

The purpose of this study is to analyze the influence of the type of recommender system on consumer's perceived benefit and privacy risk. The result showed that the perceived usefulness and intension to click was high in the order of Hybrid-filtering, Bestseller, and SNS-based system. Privacy concern was high in order of SNS-based system, Hybrid-filtering, and Bestseller. Moderating effects of perceived personalization on the type of recommender system and perceived usefulness were significant. Finally perceived usefulness had positive effect, and privacy concern had negative effect on consumer's intension to click. This study has significant implications for digital marketing bt comparing consumer responses according to the type of recommended service. The result of this study can be helpful for providing and developing future recommender service.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.777-786
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• 2018

GF (Guided Filtering) is a representative image processing technique to effectively remove noise while preserving edge information in the digital image. In this paper, we proposed a unsupervised change detection method for the KOMPSAT-3 satellite image using the GF and evaluated its performance. In order to utilize GF for the unsupervised change detection, cross-sharpened images were generated based on GF, and CVA (Change Vector Analysis) was applied to the generated cross-sharpened images to extract the changed area in the multitemporal satellite imagery. Experimental results using KOMPSAT-3 satellite images showed that the proposed method can be effectively used to detect changed regions compared with CVA results based on existing cross-sharpened images.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.98-109
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• 1988

This paper introduces an adaptive nonlinear filtering algorithm that uses the sequential regression(SER) method to update the second order Volterra filter coefficients in a recursive way. Conventionally, the SER method has been used to invert large matrices which result from direct application of Wiener filter theory to the Volterra filter. However, the algorithm proposed in this paper uses the SER approach to update the least squares solution which is derived for Gaussian input signals. In such an algorithm, the size of the matrix to be inverted is smaller than that of conventional approaches, and hence the proposed method is computationally simpler than conventional nonlinear system identification techniques. Simulation results are presented to demonstrate the performance of the proposed algorithm.

• The Journal of Society for e-Business Studies
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• v.10 no.2
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• pp.109-132
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• 2005

With the flood of multimedia contents over the digital TV channels, the internet, and etc., users sometimes have a difficulty in finding their preferred contents, spend heavy surfing time to find them, and are even very likely to miss them while searching. In this paper we suggests two-step clustering technique using time schema on how the system can recommend the user's preferred contents based on the collaborative filtering that has been proved to be successful when new users appeared. This method maps and recommends users' profile according to the gender and age at the first step, and then recommends a probabilistic item clustering customers who choose the same item at the same time based on time schema at the second stage. In addition, this has improved the accuracy of predictions in recommendation and the efficiency in time calculation by reflecting feedbacks of the result of the recommender engine and dynamically update customers' preference.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.2-17
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• 1999

Interpolated second order polynomials(ISOP's) are proposed to design efficient cascaded integrator-comb(CIC)-based decimation filters for a programmable downconverter. It is shown that some simple ISOP's can effectively reduce the passband droop caused by CIC filtering with little degradation in aliasing attenuation. In addition, ISOP's are shown to be useful for simplifying halfband filters that usually follow CIC filtering. As a result, a modified half band filter(MHBF) is introduced which is simpler than conventional halfband filters. The proposed decimation filter for a programmable downconverter is a cascade of a CIC filter, an ISOP, MHBF's and a programmable finite impulse response(FIR) filter. A procedure for designing the decimation filter is developed. In particular, an optimization technique that simultaneously designs the decimation filter is developed. In particular, an optimization technique that simultaneously designs the ISOP and programmable FIR filters is presented. Design examples demonstrate that the proposed method leads to more efficient programmable downconverters than existing ones.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.1-9
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• 2012

The popularity of digital music and smart phones led to develope noise-robust real-time audio fingerprinting system in various ways. In particular, The Multiple Hashing(MLH) of fingerprint algorithms is robust to noise and has an elaborate structure. In this paper, we propose a filter engine based on MLH to achieve better performance. In this approach, we compose a energy-intensive filter to improve the accuracy of Q/R from music database and a statistic filter to remove continuity and redundancy. The energy-intensive filter uses the Discrite Cosine Transform(DCT)'s feature gathering energy to low-order bits and the statistic filters use the correlation between searched fingerprint's information. Experimental results show that the superiority of proposed algorithm consists of the energy and statistical filtering in noise environment. It is found that the proposed filter engine achieves more robust to noise than Philips Robust Hash(PRH), and a more compact way than MLH.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.407-411
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• 2002

Ternary sequences are digital codes consisting of discrete values -1, 0, and 1 only. They are advantageous in that the correlation can be carried out using additions only. Also, they feature an ideal circular autocorrelation function, but in channel characterization tasks, the usual requirement is that the linear autocorrelation function be ideal, i.e., a Kronecker delta function. In this article, we consider two approaches to improving their linear autocorrelation or crosscorrelation properties: one is an inverse filtering method with thresholding, and the other is a singular value decomposition (SVD) method. Both methods are simulated under noisy circumstances. The inverse filtering method resulted in an improvement in peak sidelobe level of about 11 dB at an SNR of 30 dB, and the SVD method showed similar performances, albeit more sensitive to noise depending on the singular value selection strategy.