• 정보처리학회논문지B
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• 제10B권5호
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• pp.567-574
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• 2003

최근 하드웨어의 급속한 발전으로 3차원 그래픽의 적용 분야도 다양화 되어가고 있다. 3차원 가상도시를 배경으로 하는 3D MMORPG(Massive Multi-play Online Role Playing Game)와 같은 게임을 설계하기 위하여 필요한 세부 기술은 다양한 이론이 병합되어야 한다. 3D MMORPG 게임엔진은 거대한 3차원 도시의 수많은 빌딩과 개체론 실시간으로 빠르게 처리되어야 하기 때문에 렌드링의 처리뿐만 아니라 속도에 영향을 미치는 많은 요소를 가지고 있다. 이러한 게임엔진의 설계에서 중요하게 다루어지는 것은 처리 속도이다. 기존의 3D MMORPG에서 충돌검출의 방법으로 경계상자를 적용하지만 이 방법은 거대지형에서의 충돌 검출 시 속도가 느려지기 때문에 적용하기에는 바람직하지 않다. 따라서 본 논문은 거대지형상의 3D MMORPG 게임에서 발생되는 충돌검출 속도를 향상시키고자 한다. 즉 이러한 처리에서 본 논문은 다음과 같이 제시한다. 첫째 폴리곤의 충돌검사를 모두 하지 않고 빠른 시간에 충돌검출을 판단할 수 있다. 둘째 경계상자의 충돌검출에 대한 비용이 3차원 개체 개수에 대해 비례하여 증가하는 데에 대한 개선 방법을 제시한다. 그 처리 과정은 3D MMORPG 넓은 가상공간을 동적으로 처리하기 위해서는 제한적 OSP를 사용하여 공간분할을 한다. 분할된 3차원 공간을 계층적 경계상자를 이용함으로써 충돌검출에 필요한 개체를 검색하고 이론 통하여 충돌검출 속도를 개선시킬 수 있을 것이다.

• 한국항만학회지
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• 제14권3호
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1276-1279
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• 1996

Reclaimer in the raw material yard is being used to dig iron and coal so that they transfer to main blast furnace. A newly automatic system was developed and tested in the raw yard of Kwangyang iron making. The concept of the proposed system is based on the 3-dimensional detection of pile and auto-landing on the surface it.

• Journal of Multimedia Information System
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• 제9권3호
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• pp.183-190
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• 2022

Image-based 3D object detection is one of the important and difficult problems in autonomous driving and robotics, and aims to find and represent the location, dimension and orientation of the object of interest. It generates three dimensional (3D) bounding boxes with only 2D images obtained from cameras, so there is no need for devices that provide accurate depth information such as LiDAR or Radar. Image-based methods can be divided into three main categories: monocular, stereo, and multi-view 3D object detection. In this paper, we investigate the recent state-of-the-art models of the above three categories. In the multi-view 3D object detection, which appeared together with the release of the new benchmark datasets, NuScenes and Waymo, we discuss the differences from the existing monocular and stereo methods. Also, we analyze their performance and discuss the advantages and disadvantages of them. Finally, we conclude the remaining challenges and a future direction in this field.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.323-333
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• 2023

Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

• 한국소프트웨어감정평가학회 논문지
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• 제15권1호
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• pp.79-86
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• 2019

데이터의 차원축소는 요소들의 공통성을 파악해 영향력 있는 중요한 특징 요소를 추출하여 간소화함으로써 복잡함을 줄이고 다중 공선성 문제를 해결한다. 그리고 중복 및 노이즈 검출을 함으로써 불필요함을 줄인다. 이에 본 논문에서는 PCA(Prinicipal Component Analysis)을 적용한 결함 심각도 기반 차원 축소 모델을 제안한다. 제안된 모델은 결함 심각도가 있는 NASA 데이터 세트인 PC4에 적용하여 결함 심각도에 영향을 주는 속성의 차원수를 검증한다. 그 다음 데이터의 차원을 축소한 후 비교 분석한다. 실험결과, PC4의 적합한 차원수는 2~3개였고 그룹화를 통해 차원 축소가 가능한 것을 보였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2202-2205
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• 2001

This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle by steering controller.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.502-510
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• 2016

Considering video copy transform diversity, a multi-feature video copy detection algorithm based on a Speeded-Up Robust Features (SURF) local descriptor is proposed in this paper. Video copy coarse detection is done by an ordinal measure (OM) algorithm after the video is preprocessed. If the matching result is greater than the specified threshold, the video copy fine detection is done based on a SURF descriptor and a box filter is used to extract integral video. In order to improve video copy detection speed, the Hessian matrix trace of the SURF descriptor is used to pre-match, and dimension reduction is done to the traditional SURF feature vector for video matching. Our experimental results indicate that video copy detection precision and recall are greatly improved compared with traditional algorithms, and that our proposed multiple features algorithm has good robustness and discrimination accuracy, as it demonstrated that video detection speed was also improved.

• 한국생산제조학회지
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• 제8권3호
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• pp.92-99
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• 1999

The inspection unit which is developed and used in this study, is processed the shape data from the CCD camera to seek welding bite section shape, and then calculated as a real dimension from measuring the value of each inspection item. The reason of measuring with the real in this study is came out from the image method which used for a long time, which is extricated the characteristic as the dimension of pixel by recognize pixel. The measurement method of the section shape is that we decide the thresholding value after we drew the histogram to binarizate the object. After that, we make flat the object to get rid of the noise and measure the shape of welded part through the boundarization of the object. The shape measurement is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual dimension of the standard specimen and the dimension of image, to measure the ratio between the actual product and the camera image. The inspection algorithm which estimates the quality of welded product is developed and also, the software GUI(Graphic User Interface) which processes the automatic test function of the inspection system is developed. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2000년도 추계학술대회논문집
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• pp.207-217
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are angle, distance error and real position of other vehicles, we should calculate the reference steering angle.