• Title/Summary/Keyword: 검출 모델

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Face Detection based on Multi-Channel Skin-Color Model (다채널 피부색 모델에 기반한 얼굴 영역 검출)

  • 김영권;고재필;변혜란
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.433-435
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    • 2001
  • 얼굴 인식분야에서 실시간 얼굴검출에 대한 관심이 높아짐에 따라 피부색컬러 모델을 통한 얼굴영역검출에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 피부색 모델은 밝기 정보를 제거한 단일 채널의 색상모델이 대부분이다. 이에 본 논문에서는 얼굴피부색을 보다 효과적으로 모델링하기 위하여, 피부색 특성을 고려하여, 밝기 성분을 제거한 RGB 컬러를 모두 사용하는 H, Cb, Cg의 다채널 피부색 모델을 제시한다. 또한, 색상정보에서 사용하지 않은 밝기 정보는 영상 분할을 통해 사용한다. 제안하는 피부색 모델을 통한 얼굴영역 추출 과정을 보인다.

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A Study on Keyword Spotting System Using Pseudo N-gram Language Model (의사 N-gram 언어모델을 이용한 핵심어 검출 시스템에 관한 연구)

  • 이여송;김주곤;정현열
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.3
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    • pp.242-247
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    • 2004
  • Conventional keyword spotting systems use the connected word recognition network consisted by keyword models and filler models in keyword spotting. This is why the system can not construct the language models of word appearance effectively for detecting keywords in large vocabulary continuous speech recognition system with large text data. In this paper to solve this problem, we propose a keyword spotting system using pseudo N-gram language model for detecting key-words and investigate the performance of the system upon the changes of the frequencies of appearances of both keywords and filler models. As the results, when the Unigram probability of keywords and filler models were set to 0.2, 0.8, the experimental results showed that CA (Correctly Accept for In-Vocabulary) and CR (Correctly Reject for Out-Of-Vocabulary) were 91.1% and 91.7% respectively, which means that our proposed system can get 14% of improved average CA-CR performance than conventional methods in ERR (Error Reduction Rate).

스마트폰 음성 통신용 음성 검출 기술

  • Kim, Sang-Gyun;Jang, Jun-Hyeok
    • Information and Communications Magazine
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    • v.29 no.4
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    • pp.10-14
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    • 2012
  • 본고에서는 스마트폰 환경에서 음성 통신에 필요한 가변 전송률 음성 부호화기를 위한 음성 검출 기술을 알아본다. 소개할 음성 검출 기술은 통계적 모델(statistical model)을 기반으로 한 우도비 테스트(likelihood ratio test, LRT)를 이용하여 음성 존재 여부를 판단하는 결정법을 유도한다. 이후 통계적 모델을 기반으로 한 음성 검출 방법의 신뢰도를 높이기 위해 새로운 방법들이 연구되었으며 최근까지 연구가 진행 중인 통계적 모델 기반의 음성 검출 방법을 소개한다.

Statistical Model-Based Voice Activity Detection Using the Second-Order Conditional Maximum a Posteriori Criterion with Adapted Threshold (적응형 문턱값을 가지는 2차 조건 사후 최대 확률을 이용한 통계적 모델 기반의 음성 검출기)

  • Kim, Sang-Kyun;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.1
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    • pp.76-81
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    • 2010
  • In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

Integrated 3D Skin Color Model for Robust Skin Color Detection of Various Races (강건한 다인종 얼굴 검출을 위한 통합 3D 피부색 모델)

  • Park, Gyeong-Mi;Kim, Young-Bong
    • The Journal of the Korea Contents Association
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    • v.9 no.5
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    • pp.1-12
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    • 2009
  • The correct detection of skin color is an important preliminary process in fields of face detection and human motion analysis. It is generally performed by three steps: transforming the pixel color to a non-RGB color space, dropping the illuminance component of skin color, and classifying the pixels by the skin color distribution model. Skin detection depends on by various factors such as color space, presence of the illumination, skin modeling method. In this paper we propose a 3d skin color model that can segment pixels with several ethnic skin color from images with various illumination condition and complicated backgrounds. This proposed skin color model are formed with each components(Y, Cb, Cr) which transform pixel color to YCbCr color space. In order to segment the skin color of several ethnic groups together, we first create the skin color model of each ethnic group, and then merge the skin color model using its skin color probability. Further, proposed model makes several steps of skin color areas that can help to classify proper skin color areas using small training data.

Optimization of Design Variables of Detection Algorithm for Loss of Balance Using a Linear Internal Model (균형상실의 검출 성능 향상을 위한 내부 모델의 설계변수 선정 및 민감도 평가)

  • Kim, Kwang-Hoon;Kim, In-Su;Son, Kwon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.9
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    • pp.1153-1160
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    • 2010
  • The detection algorithm for loss of balance had three main parts: one for processing data, another for constructing an internal model, and a third for detecting the loss of balance. The part related to the internal model is the most important part of the algorithm. The purpose of this study is to evaluate the effect of variables associated with the internal model on the success rate of the algorithm. The internal model depends on the type of linearization adopted and the operating period of the algorithm. The design variables were evaluated by performing sensitivity analysis of the variables of the internal model in order to obtain the success rate of the algorithm. The results showed that the most sensitive variable was the period and the period of 0.3 s yielded the highest success rate of 97.1%. Further, the ranges of the design variables that can facilitate a success rate of over 95% are presented.

Satellite Fault Detection and Isolation Using 2 Step IMM (2 단계 상호간섭 다중모델을 이용한 인공위성 고장 검출)

  • Lee, Jun-Han;Park, Chan-Gook;Lee, Dal-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.39 no.2
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    • pp.144-152
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    • 2011
  • This paper presents a new scheme for fault detection and isolation in the satellite system. The purpose of this paper is to develop a fault detection, isolation and diagnosis algorithm based on the bank of interacting multiple model (IMM) filter for both total and partial faults in a satellite attitude control system (ACS). In this paper, IMM are utilized for detection and diagnosis of anticipated actuator faults in a satellite ACS. Other fault detection, isolation (FDI) schemes using conventional IMM are compared with the proposed FDI scheme. The FDI procedure is developed in two stages. In the first stage, 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the second stage of the FDI scheme, two filters are designed to identify the fault type which is either the total or partial fault. An important feature of the proposed FDI scheme can decrease fault isolation time and figure out not only fault detection and isolation but also fault type identification.

A Study on Detectors and Interference Models for 2-D OCDMA Networks (2-D OCDMA LAN에서의 검출기와 간섭 모델의 성능에 대한 비교 연구)

  • Yun, Yong-Chul;Choe, Jin-Woo;Sung, Won-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.4B
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    • pp.245-256
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    • 2003
  • 2-D OCDMA is considered to be a viable technical solution for optical LANs, and a considerable amount of research effort has been devoted to various 2-D OCDMA techniques. In this paper, we propose two new interference model for 2-D OCDMA LANs employing unipolar random codes, and derive maximum-likelihood detectors based on these interference models. The BER performance of the maximum likelihood detectors and that of other existing detectors are compared through extensive computer simulation. In addition, the complexity of high-speed implementation of the detectors is assessed, and as a result, we found that the AND detector and the maximum-likelihood detectors for the pulse-binomial and the pulse-Poisson model offer the best trade-off between the BER performance and the facility of high-speed implementation.

Character spotting using image-based stochastic models (이미지 기반 확률모델을 이용한 문자검출)

  • 김선규;신봉기
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.484-486
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    • 2001
  • 본 논문에서는 의사 2차원 은닉 마르코프 모델의 구조로 생성한 마르코프 체인형 확률모형에 의한 인쇄체문자 이미지의 모델링에 대해 논한다. 이미지 데이터에서 바로 모델을 실시간 생성하며 문자 인식 및 검출에 응용할 수 있다. 실험에 의하면, 이 방법을 통해 특정 낱말이 포함된 문장에서 숫자를 인식, 한글을 검출할 수 있음을 확인하였다.

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Lightweight Key Point Detection Model Based on Multi-Scale Ghost Convolution for YOLOv8 (YOLOv8 을 위한 다중 스케일 Ghost 컨볼루션 기반 경량 키포인트 검출 모델)

  • Zihao Li;Inwhee Joe
    • Annual Conference of KIPS
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    • 2024.05a
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    • pp.604-606
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    • 2024
  • 컴퓨터 비전 응용은 우리 생활에서 중요한 역할을 한다. 현재, 대규모 모델의 등장으로 딥 러닝의 훈련 및 운행 비용이 급격히 상승하고 있다. 자원이 제한된 환경에서는 일부 AI 프로그램을 실행할 수 없게 되므로, 경량화 연구가 필요하다. YOLOv8 은 현재 주요 목표 검출 모델 중 하나이며, 본 논문은 다중 스케일 Ghost 컨볼루션 모듈을 사용하여 구축된 새로운 YOLOv8-pose-msg 키포인트 검출 모델을 제안한다. 다양한 사양에서 새 모델의 매개변수 양은 최소 34% 감소할 수 있으며, 최대 59%까지 감소할 수 있다. 종합적인 검출 성능은 비교적 대규모 데이터셋에서 원래의 수준을 유지할 수 있으며, 소규모 데이터셋에서의 키포인트 검출은 30% 이상 증가할 수 있다. 동시에 최대 25%의 훈련 및 추론 시간을 절약할 수 있다.