• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.109-114
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• 2011

To estimate sound direction of arrival with a pair of microphones, a method based on Time Difference of Arrival (TDOA) estimation using the Cross Power Spectrum Phase (CPSP) function is largely used due to its simplicity and good performance. In this paper, we investigate CPSP maximum values for various SNRs and adverse environments, and propose a novel method to improve the estimation performance of sound direction of arrival. The proposed method applies a threshold to the CPSP values and increases the reliability of the estimated sound direction. Through computer simulation for various SNRs, we validate the effectiveness of the proposed method. When the threshold was set to 0.1, more than 90% of success rate of sound direction of arrival estimation has been achieved for directions of $10^{\circ}$, $40^{\circ}$, $70^{\circ}$ from the source location even with reverberation times of 0.1s.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.3
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• pp.163-175
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• 1996

This paper invetigates estimation methods of mapping parameters in object-oriented coding. In this paper, we propose a fast parameter estimation method with its performance similar to that of the conventional methods. We employ hierarchical structure in difference images to redcue the computational complexity and also combine conventional six- and eight-mapping parameter estimation methods to compensate for the performance degradation caused by employment of hierarchical structure. Computer simulation shows that the proposed mehtod gives results similar to conventional methods with greatly reduced computational complexity.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.61-63
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• 1994

Accurate estimation of soil resistivity parameters are very important in the design of grounding systems. This paper presents a useful methodology for the optimal estimation of soil parameters based on the weighted least square concepts using a set of earth resistivity measurements by Wenner method. And, this paper developes a computer simulation programming for the estimation of soil parameters. Results are presented and compared with the results of other methods.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.119-124
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• 1996

Variable step size LMS(VS-LMS) algorithms improve performance of LMS algorithm by means of varying the step size. This paper presents a new VS-LMS algorithm using normalized absolute estimation error. Normalizing the estimation error to the expected valus of the desired signal, we determined the step size using the relative size of estimation error, Because parameters and computational load are less, our algorithm is easy to implement in hardware. The performance of the proposed algorithm is analyzed theoretically and estimated through simulations. Based on the theoretical analysis and computer simulations, the proposed algorithm is shown to be effective compared to conventional VS-LMS algorithms.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.89-99
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• 2016

One of the fundamental elements in developing mixed reality applications is to effectively analyze and apply the environmental lighting information to image synthesis. In particular, interactive applications require to process dynamically varying lighting sources in real-time, reflecting them properly in rendering results. Previous related works are not often appropriate for this because they are usually designed to synthesize photorealistic images, generating too many, often exponentially increasing, light sources or having too heavy a computational complexity. In this paper, we present a fast light source estimation technique that aims to search for primary light sources on the fly from a sequence of video images taken by a camera equipped with a fisheye lens. In contrast to previous methods, our technique can adust the number of found light sources approximately to the size that a user specifies. Thus, it can be effectively used in Phong-illumination-model-based direct illumination or soft shadow generation through light sampling over area lights.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.61-71
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• 2018

When triangular meshes are generated from the point clouds in global space reconstructed through camera pose estimation against captured RGB-D streams, the quality of the resulting meshes improves as more triangles are hired. However, for 3D reconstructed models beyond some size threshold, they become to suffer from the ugly-looking artefacts due to the insufficient precision of RGB-D sensors as well as significant burdens in memory requirement and rendering cost. In this paper, for the generation of 3D models appropriate for real-time applications, we propose an effective technique that extracts high-quality textures for moderate-sized meshes from the captured colors associated with the reconstructed point sets. In particular, we show that via a simple method based on the mapping between the 3D global space resulting from the camera pose estimation and the 2D texture space, textures can be generated effectively for the 3D models reconstructed from captured RGB-D image streams.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1439-1444
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• 2015

Measuring spectral reflectance can be regarded as obtaining inherent color parameters, and spectral reflectance has been used in image processing. Model-based spectrum recovering, one of the method for obtaining spectral reflectance, uses ordinary camera with multiple illuminations. Conventional model-based methods allow to recover spectral reflectance efficiently by using only a few parameters, however it requires some parameters such as power spectrum of illuminations and spectrum sensitivity of camera. In this paper, we propose an enhanced model-based spectrum recovering method without pre-measured parameters: power spectrum of illuminations and spectrum sensitivity of camera. Instead of measuring each parameters, spectral reflectance can be efficiently recovered by estimating and using the spectrum characteristic matrix which contains spectrum parameters: basis function, power spectrum of illumination, and spectrum sensitivity of camera. The spectrum characteristic matrix can be easily estimated using captured images from scenes with color checker under multiple illuminations. Additionally, we suggest fast recovering method preserving positive constraint of spectrum by nonnegative basis function of spectral reflectance. Results of our method showed accurately reconstructed spectral reflectance and fast constrained estimation with unmeasured camera and illumination. As our method could be conducted conveniently, measuring spectral reflectance is expected to be widely used.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.39-47
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• 2008

In this research, a web-based design support system is constructed for the design process of automotive steel pulley to gather engineering knowledge from pulley design data. In the design search module, a clustering tool for design data is proposed using K-means clustering algorithm. To obtain correlational patterns between design and FEA (Finite Element Analysis) data, a Multi-layer Back Propagation Network (MBPN) is applied. With the analyzed patterns from a number of simulation data, an estimation of minimum von mises can be provided for given design parameters of pulleys. The case study revealed fast estimation of minimum stress in the pulley within 12% error.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.203-210
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• 2013

Majority of the wireless ad hoc routing protocols are proposed to find feasible routes without considering the network load, end-to-end link quality and bandwidth requirements of the application. Therefore, protocol may not provide sufficient quality of service (QoS) to a high speed traffic such as multimedia. In this paper, we propose a path-quality and bandwidth-estimation based routing protocol (PBBR) for the high quality multimedia stream that can meet the application's bandwidth requirements and find the best reliable route. The novelty of this protocol is to select a reliable path to respond the application's requirements based on available bandwidth at each intermediate node and end-to-end path loss ratio. Obtained results from the simulation demonstrates that our protocol can achieve sufficient performance in terms of throughput and end-to-end delay.