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영상 데이터의 입체화 및 합성 기반 실감 콘텐츠 생성 기법
김만배(Manbae Kim),홍동희(Donghee Hong),조영란(Youngran Cho),김학수(Haksoo Kim) 한국방송·미디어공학회 2004 방송공학회논문지 Vol.9 No.4
Recently, there has been much interest in realistic broadcasting that is a new field following HDTV and 3DTV. In general, the realistic broadcasting is composed of diverse components such as aquisition, authoring, compression, transmission and display, posing many challenging tasks. It is necessary that the types of realistic contents need to be defined prior to the development of realistic broadcasting systems. Based upon them, other components need to be designed and developed. In this paper, we propose some realistic contents suitable to the realistic broadcasting as well as techniques of generating them. Our proposed contents consist of stereoscopic multiview sequences, object-based stereoscopic images, depth map-based image compositing and the composition of stereoscopic real and graphics images. Content generation techniques and their associated software modules are presented with realistic images produced from our experiments. Those contents are produced to deliver stereoscopic perception, immersion and realism to the users as shown in our experimental results.
합성곱 신경망을 이용하는 수퍼픽셀 기반 사과잎 병충해의 분류
김만배(Manbae Kim),최창열(Changyeol Choi) 한국방송·미디어공학회 2020 방송공학회논문지 Vol.25 No.2
The classification of plant diseases by images captured by a camera sensor has been studied over past decades. A method that has gained much interest is to use image segmentation, from which statistical features are derived and analyzed by machine learning. Recently, deep learning has been adopted in this area. However, image segmentation is still a difficult task to achieve stable performance due to a variety of environmental variations. The end-to-end learning in neural network has a demerit that train images may be different from real images acquired in outdoor fields. To solve these problems, we propose superpixel-based disease classification method using end-to-end CNN (convolutional neural network) learning. Based on experiments performed on PlantVillage apple images, the classification accuracy is 98.29% and 92.43% for full-image and superpixel. As well, the multivariate F1-score is (0.98, 0.93). Therefore we validate that the method of using superpixel is comparable to that of full-image.
Generation of Stereoscopic Image from 2D Image based on Saliency and Edge Modeling
Manbae Kim(김만배) 한국방송·미디어공학회 2015 방송공학회논문지 Vol.20 No.3
3D conversion technology has been studied over past decades and integrated to commercial 3D displays and 3DTVs. The 3D conversion plays an important role in the augmented functionality of three-dimensional television (3DTV), because it can easily provide 3D contents. Generally, depth cues extracted from a static image is used for generating a depth map followed by DIBR (Depth Image Based Rendering) rendering for producing a stereoscopic image. However except some particular images, the existence of depth cues is rare so that the consistent quality of a depth map cannot be accordingly guaranteed. Therefore, it is imperative to make a 3D conversion method that produces satisfactory and consistent 3D for diverse video contents. From this viewpoint, this paper proposes a novel method with applicability to general types of image. For this, saliency as well as edge is utilized. To generate a depth map, geometric perspective, affinity model and binomic filter are used. In the experiments, the proposed method was performed on 24 video clips with a variety of contents. From a subjective test for 3D perception and visual fatigue, satisfactory and comfortable viewing of 3D contents was validated.
김만배(Manbae Kim) 한국방송·미디어공학회 2021 방송공학회논문지 Vol.26 No.5
The arc is one of factors causing electrical fires. Over past decades, various researches have been carried out to detect arc occurrences. Even though frequency analysis, wavelet and statistical features have been used, arc detection performance is degraded due to diverse arc waveforms. On the contray, Deep neural network (DNN) direcly utilizes raw data without feature extraction, based on end-to-end learning. However, a disadvantage of the DNN is processing complexity, posing the difficulty of being migrated into a termnial device. To solve this, this paper proposes an arc detection method using a logistic regression that is one of simple machine learning methods.
증발기로 사용되는 판형열교환기의 건도 변화에 따른 열전달 및 압력강하 특성에 관한 실험적 연구
김만배(Manbae Kim),박창용(Changyong Park) 대한설비공학회 2016 대한설비공학회 학술발표대회논문집 Vol.2016 No.6
The In this study, the heat transfer and pressure drop characteristics were measureed for a brazed plate heat exchanger (BPHE) operated as an evaporator. The plate pattern of the BPHE was a chevron type and its number of plate was 10. The working fluid was R22 as a refrigerant and water was cooled in the BPHE. For the measurement of the evaporation characteristics, the evaporation temperature was set about 20℃ and the mass flux was controlled about 35 ㎏/㎡s . The average vapor quality was controlled at the range of 0.15-0.6. The average heat transfer coefficients decreased significantly over the vapor quality of 0.5. However, the pressure drop continuously increased to the vapor quality up to 0.6. The measured heat transfer coefficients before the vapor quality of 0.5 ware higher than the calculated values by the previously proposed correlations for the plate heat exchangers with evaporation, which could be caused by the smaller hydraulic diameter of the tested BPHE.
단일 엔코더 및 디코더를 이용하는 다시점 비디오 시스템
김학수(Haksoo Kim),김윤(Yoon Kim),김만배(Manbae Kim) 한국방송·미디어공학회 2006 방송공학회논문지 Vol.11 No.1
The progress of data transmission technology through the Internet has spread a variety of realistic contents. One of such contents is multi-view video that is acquired from multiple camera sensors. In general, the multi-view video processing requires encoders and decoders as many as the number of cameras, and thus the processing complexity results in difficulties of practical implementation. To solve for this problem, this paper considers a simple multi-view system utilizing a single encoder and a single decoder. In the encoder side, input multi-view YUV sequences are combined on GOP units by a video mixer. Then, the mixed sequence is compressed by a single H.264/AVC encoder. The decoding is composed of a single decoder and a scheduler controling the decoding process. The goal of the scheduler is to assign approximately identical number of decoded frames to each view sequence by estimating the decoder utilization of a GOP and subsequently applying frame skip algorithms. Furthermore, in the frame skip, efficient frame selection algorithms are studied for H.264/AVC baseline and main profiles based upon a cost function that is related to perceived video quality. Our proposed method has been performed on various multi-view test sequences adopted by MPEG 3DAV. Experimental results show that approximately identical decoder utilization is achieved for each view sequence so that each view sequence is fairly displayed. As well, the performance of the proposed method is examined in terms of bit-rate and PSNR using a rate-distortion curve.