• Journal of KIISE
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• v.43 no.1
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• pp.13-26
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• 2016

This paper proposes a new sound localization algorithm that can improve localization performance based on a tetrahedron-shaped microphone array. Sound localization system estimates directional information of sound source based on the time delay of arrival(TDOA) information between the microphone pairs in a microphone array. In order to obtain directional information of the sound source in three dimensions, the system requires at least three microphones. If one of the microphones fails to detect proper signal level, the system cannot produce a reliable estimate. This paper proposes a tetrahedron- shaped sound localization system with a coordinate transform method by adding one microphone to the previously known triangular-shaped system providing more robust and reliable sound localization. To verify the performance of the proposed algorithm, a real time simulation was conducted, and the results were compared to the previously known triangular-shaped system. From the simulation results, the proposed tetrahedron-shaped sound localization system is superior to the triangular-shaped system by more than 46% for maximum sound source detection.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.53-56
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• 2006

최근 가정용 로봇 연구가 활발히 진행됨에 따라, 가정과 같은 다이내믹한 환경에서 로봇이 목소리를 포함한 음원에 반응하고 그 위치를 정확히 찾아가는 것이 매우 중요해지고 있다. 인간이 목표물에 도달하기 위해 경로를 선택할 때, 그 목표물이 소리인 경우는 현재 위치에서 음원의 방향을 추적한다. 또한 그 목표물의 위치가 지도로 주워질 경우에는 현재 위치와 목표불의 절대적 방위를 기준으로 추적한다. 본 논문에서는 이처럼 사람이 다른 사람의 목소리를 듣고 반응하거나 어떤 방향으로 가고자할 때 소리가 나는 방향이나 지도를 통해 대략 자신만의 방위를 만드는 것에 착안하여, 지능형 모바일 로봇에 음원추적 장치와 전자나침반을 장착함으로써 음원의 방향 또는 절대 방위를 기준으로 목표물을 찾아가는 알고리즘을 제시하고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.21-24
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• 2007

보안이 중요시되는 공간에서 임의의 사람을 추적하고 인식할 수 있는 시스템의 필요성이 점차 중요시되고 있다. 본 논문에서는 wide-area를 감시하기 위해 음원과 Pan-Tilt 카메라를 이용하여 침입자 추적 시스템을 구현하고자 한다. 먼저 음원 추적 센서를 이용하여 음원의 방위를 검출한 후 Pan-Tilt 카메라를 방위 방향으로 이동시키고 이동된 Pan-Tilt 카메라로부터 기준영상을 추출한 후 일정 기준 시간마다 영상을 다시 획득하여 차 영상과 검출결과를 얻어 침입자를 추적하여 감시 시스템을 구현한다. 본 논문에 의해서 구현된 시스템은 홈 네트워크 보안 시스템과 연동을 하여 가정이나 공공시설 보안에 대한 인터페이스 역할을 할 수 있다.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.4
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• pp.227-232
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• 2007

인간과 상호작용하는 로봇의 경우, 자연스러운 움직임과 행동은 사람에게 친근감을 제공한다. 그러한 자연스러운 움직임과 행동의 기반이 되는 요소기술들 중 하나로 음원추적을 꼽을 수 있다. 본 논문에서는 3개의 마이크를 장착한 로봇에서의 시간지연기반 음원추적 시스템에 대해 소개한다. 개발된 음원추적 시스템을 지능형 서비스 로봇 WEVER-R2에 적용한 결과, 에러율 ${\pm}15$도 이내에서 93% 이상의 성공률을 보였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.519-525
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• 2007

With the high interest on robot technology and application, the research on artificial auditory systems for robot is very active. In this paper we discuss sound source localization and tracing based on audio-visual information. For video signals we use face detection based on skin color model. Also, binaural-based DOA is used as audio information. We integrate both informations using Kalman filter. The experimental results show that audio-visual person tracking Is useful, specially in the case that some informations are not observed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.708-717
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• 2017

Tracking of sound-location is widely used in various area such as intelligent CCTV, video conference and voice commander. In this paper we introduce the real-time sound-location tracking method for smart lecture system using TDoA(Time Difference of Arrival) with orthogonal microphone array on the ceiling. Through discussion on some models of TDoA detection, cross correlation method using linear microphone array is proposed. Orthogonal array with 5 microphone could detect omni direction of sound-location. For real-time detection we adopt the threshold of received energy for eliminating no-voice interval, signed cross correlation for reducing computational complexity. The detected azimuth angles are processed using median filter for lowering the angle deviation. The proposed system is implemented with high performance MCU of TMS320F379D and MEMs microphone module and shows the accuracy of 0.5 and 6.5 in degree for white noise and lectured voice, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.532-537
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• 2009

The necessity of intelligent surveillance system is gradually considered seriously from the space where the security is important. In this paper, we embodied unmanned intelligent system by developing embedded mobile robot based on images and sounds tracking. For objects tracking, we used block-matching algorithm and for sound source tracking, we calculated time differences and magnitude dissimilarities of sound. And we demonstrated the superiority of intruder tracking algorithm through the embodiment of Pan-Tilt camera and sound source tracking module using system, Network camera and mobile robot using system and mobile robot using system. By linking security system, the suggested system can provide some interfacing functions for the security service of the public facilities as well as that of home.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.

• The Journal of the Acoustical Society of Korea
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• v.24 no.6
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• pp.303-308
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• 2005

In this paper, the acoustic properties of the light bulb are presented based on a new light bulb source system of continuously transmitting implosive signal . We describe the results of analysis of bulb signals and comparison with Previous works. The results show that Peak-source-level and Primary resonant frequency are increasing with increasing source depth. This bulb source can be used for the purpose of geoacoustic parameter inversion and source tracking in sha]low water via matched field processing.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.759-766
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• 2016

This paper is on a system design of recognizing sound sources and tracing locations from detecting a section of sound sources which is strong in surrounding environmental sounds about sound sources occurring in an abnormal situation by using signals within the section. In detection of the section with strong sound sources, weighted average delta energy of a short section is calculated from audio signals received. After inputting it into a low-pass filter, through comparison of values of the output result, a section strong in background sound is defined. In recognition of sound sources, from data of the detected section, using an HMM(: Hidden Markov Model) as a traditional recognition method, learning and recognition are realized from creating information to recognize sound sources. About signals of sound sources that surrounding background sounds are included, by using energy of existing signals, after detecting the section, compared with the recognition through the HMM, a recognition rate of 3.94% increase is shown. Also, based on the recognition result, location grasping by using TDOA(: Time Delay of Arrival) between signals in the section accords with 97.44% of angles of a real occurrence location.