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Hwang, Sungmok,Park, Youngjin American Institute of Physics for the Acoustical S 2008 Journal of the Acoustical Society of America Vol.123 No.4
<P>A principal components analysis of the median-plane head-related impulse responses (HRIRs) in the CIPIC HRTF database reveals that the individual HRIRs can be reconstructed by a linear combination of 12 principal components (PCs) within 5% of error in the least-squares sense. The PCs include the intersubject and interelevation variations in the median-plane HRIRs. Each PC provides sound cues for the front-back discrimination and/or the vertical perception. There exist common systematic elevation dependencies in the weights of lower-numbered PCs which contribute to the pinna/head diffractions, whereas the elevation dependencies in the weights of higher-numbered PCs are different from subject to subject.</P>
Modeling and Customization of Head-Related Transfer Functions using Principal Component Analysis
Sungmok Hwang,Youngjin Park,Youn-sik Park 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
This study deals with modeling and customization of head-related transfer functions (HRTFs) in the median plane based on a weighted linear summation of a set of general basis functions obtained from a specific huge HRTF database. The 12 principal components (PCs) were extracted from principal components analysis of the median-plane HRTFs in the CIPIC HRTF database. It was verified that the 12 PCs can be general basis functions to model arbitrary subject’ median-plane HRIRs, which are not included in the process to obtain the basis functions, through the quantitative analysis on the modeling error in the least-squares sense and the subjective listening tests. A HRTF customization method based on subjective tuning of the general basis functions was proposed. In the subjective listening test results, all subjects reported better performances for the vertical perception and the front-back discrimination with the customized HRTFs than those with the non-individualized HRTFs except for the front-back confusions of one subject.
Multiple Subarea Pose Models based Top-view People Detection for Smart Home System
Sungmok Hwang(황석목),Taeyup Song(송태엽),Sangyun Kim(김상윤),Seungmyun Baek(백승면),Dubok Park(박두복),Hanseok Ko(고한석) 대한전자공학회 2017 대한전자공학회 학술대회 Vol.2017 No.6
본 논문에서는 평면 시점에서 촬영된 영상에서 효과적인 사람 검출을 위한 다중 영역 자세 모델을 이용한 사람 검출 기술을 제안한다. 제안된 기술은 3가지 단계로 첫 번째로 밝기 변화에 대응하기 위해 히스토그램의 상/하한 문턱값 및 감마 보정을 통한 밝기 보정 기술, 다음으로 다중 영역별 자세 모델을 이용한 사람 검출기술, 마지막으로 카오스 이론 기반의 움직임 측정을 통한 검출결과 정련 기술로 구성된다. 실험 결과를 통해 제안된 방법은 단일 자세 모델기반의 사람 검출 기술에 비해 향상된 성능을 보이는 것을 확인할 수 있다.