서지주요정보
칼만 필터링과 선형 불변을 이용한 차량의 검지와 인식 = Vehicle detection and recognition using Kalman filtering and affine invariant
서명 / 저자 칼만 필터링과 선형 불변을 이용한 차량의 검지와 인식 = Vehicle detection and recognition using Kalman filtering and affine invariant / 박영준.
저자명 박영준 ; Park, Young-Joon
발행사항 [대전 : 한국과학기술원, 1997].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8007115

소장위치/청구기호

학술문화관(문화관) 보존서고

MADE 97013

SMS전송

도서상태

이용가능

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반납예정일

초록정보

Vehicle detection and recognition are very important issues in vision-based traffic applications. We are interested in detecting and recognizing moving vehicles in real road scenes captured by a static camera. An image difference based method is adopted for the segmentation of moving vehicles from input road images. Therefore, the exact background image is needed for successful vehicle detection. We used a Kalman filter based concept to obtain and continuously update the background image. We propose a new technique which adaptively determines the Kalman gain by using the Mahalanobis distance. Motion detection process consists of the initial mode for obtaining an approximate background image and the detection mode for segmenting moving vehicles as a next step. Then recognition is performed only within regions where a moving objects are detected. As an off-line process, we build model set, including three typical vehicle types sedan, jeep, and bus, directly from the input image. In next step, we find the vehicle roof by maximizing an energy function defined by edge, line reliability and corner reliability. Using four lines of the roof as the bases of canonical coordinate we calculate five-line invariant of other lines. Finally we recognize the moving vehicle from the model set using five lines invariants.

서지기타정보

서지기타정보
청구기호 {MADE 97013
형태사항 v, 66 p. : 삽도 ; 26 cm
언어 한국어
일반주기 부록 : A, 차종별 불변량 통계 자료. - B, 시뮬레이션 프로그램
저자명의 영문표기 : Young-Joon Park
지도교수의 한글표기 : 권인소
지도교수의 영문표기 : In-So Kweon
학위논문 학위논문(석사) - 한국과학기술원 : 자동화및설계공학과,
서지주기 참고문헌 : p. 58-59
주제 변화 검지
적응 칼만 이득
지붕 검지
다섯 직선의 불변량
Change detection
Adaptive kalman gain
Roof detection
Five-line invariant
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