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RISS 인기검색어
- 검색키워드
- 저자 : 주영훈(Yung Hoon Joo) (검색결과 5 건)
- 무료
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유사한 색상을 지닌 다수의 이동 물체 영역 분류 및 식별과 추적
이정식(Jung Sik Lee),주영훈(Yung Hoon Joo) 대한전기학회 2016 전기학회논문지 Vol.65 No.3
This paper presents the area classification, identification, and tracking for multiple moving objects with the similar colors. To do this, first, we use the GMM(Gaussian Mixture Model)-based background modeling method to detect the moving objects. Second, we propose the use of the binary and morphology of image in order to eliminate the shadow and noise in case of detection of the moving object. Third, we recognize ROI(region of interest) of the moving object through labeling method. And, we propose the area classification method to remove the background from the detected moving objects and the novel method for identifying the classified moving area. Also, we propose the method for tracking the identified moving object using Kalman filter. To the end, we propose the effective tracking method when detecting the multiple objects with the similar colors. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.
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[컴퓨터지능 및 지능시스템] DTW 알고리즘을 이용한 다중 이동 객체 추적 방법
왕교선(Kyo Sun Wang),주영훈(Yung Hoon Joo) 대한전기학회 2019 전기학회논문지 Vol.68 No.5
In this paper, we propose a method to track multiple moving objects using DTW algorithm for images received from CCTV Cameras. The proposed method first extracts a moving object using GMM background modeling to extract a moving object from the input image, and then removes and extends the shadow and noise of the extracted moving object using morphology. The moving object thus obtained is recognized by using the labeling method, and the labeling is merged using the morphology to identify the problem that the recognized moving object is divided into several labels. Then, when the recognized moving object is detected in the designated ROI, the HSV and RGB values of the moving object are extracted and the extracted data is sequentially stored in the DTW data base. Next, we propose a method of classifying the moving object as similar to the DTW by judging the similarity between the stored DTW DB and the moving object. The moving objects classified by the proposed method are continuously compared and tracked. If it is judged that the moving objects to be tracked are overlapped, it is possible to compare the remaining objects. It also suggests how tracking can be done if the moving object is unwrapped. Finally, the applicability of the proposed method is verified through various experiments.
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골격 특징 및 색상 유사도를 이용한 가축 도난 감지 시스템
김준형(Jun Hyoung Kim),주영훈(Yung Hoon Joo) 대한전기학회 2018 전기학회논문지 Vol.67 No.4
In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.
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형태학적 특징 기반 모델을 이용한 가축 도난 판단 시스템
김준형(Jun Hyoung Kim),주영훈(Yung Hoon Joo) 대한전기학회 2018 전기학회논문지 Vol.67 No.4
In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.
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이동물체들의 Optical flow와 EMD 알고리즘을 이용한 식별과 Kalman 필터를 이용한 추적
이정식(Jung Sik Lee),주영훈(Yung Hoon Joo) 대한전기학회 2015 전기학회논문지 Vol.64 No.7
We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.
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