• Title/Summary/Keyword: Object Color

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Real-Time Image-Based Relighting for Tangible Video Teleconference (실감화상통신을 위한 실시간 재조명 기술)

  • Ryu, Sae-Woon;Parka, Jong-Il
    • Journal of Broadcast Engineering
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    • v.14 no.6
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    • pp.807-810
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    • 2009
  • This paper deals with a real-time image based relighting system for tangible video teleconference. The proposed image based relighting system renders the extracted human object using the virtual environmental images. The proposed system can homogenize virtually the lighting environments of remote users on the video teleconference, or render the humans like they are in the virtual places. To realize the video teleconference, the paper obtains the 3D object models of users in real-time using the controlled lighting system. In this paper, we use single color camera and synchronized two directional flash lights. Proposed system generates pure shading images using on and off flash images subtraction. One pure shading reflectance map generates a directional normal map from multiplication of each reflectance map and basic normal vector map. Each directional basic normal map is generated by inner vector calculation of incident light vector and camera viewing vector. And the basic normal vector means a basis component of real surface normal vector. The proposed system enables the users to immerse video teleconference just as they are in the virtual environments.

Video Segmentation using the Level Set Method (Level Set 방법을 이용한 영상분할 알고리즘)

  • 김대희;호요성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.5
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    • pp.303-311
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    • 2003
  • Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video object from natural video sequences. Segmentation algorithms can largely be classified into automatic segmentation and user-assisted segmentation. In this paper, we propose a user-assisted VOP generation method based on the geometric active contour. Since the geometric active contour, unlike the parametric active contour, employs the level set method to evolve the curve, we can draw the initial curve independent of the shape of the object. In order to generate the edge function from a smoothed image, we propose a vector-valued diffusion process in the LUV color space. We also present a discrete 3-D diffusion model for easy implementation. By combining the curve shrinkage in the vector field space with the curve expansion in the empty vector space, we can make accurate extraction of visual objects from video sequences.

Real-time Identification of Traffic Light and Road Sign for the Next Generation Video-Based Navigation System (차세대 실감 내비게이션을 위한 실시간 신호등 및 표지판 객체 인식)

  • Kim, Yong-Kwon;Lee, Ki-Sung;Cho, Seong-Ik;Park, Jeong-Ho;Choi, Kyoung-Ho
    • Journal of Korea Spatial Information System Society
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    • v.10 no.2
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    • pp.13-24
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    • 2008
  • A next generation video based car navigation is researched to supplement the drawbacks of existed 2D based navigation and to provide the various services for safety driving. The components of this navigation system could be a load object database, identification module for load lines, and crossroad identification module, etc. In this paper, we proposed the traffic lights and road sign recognition method which can be effectively exploited for crossroad recognition in video-based car navigation systems. The method uses object color information and other spatial features in the video image. The results show average 90% recognition rate from 30m to 60m distance for traffic lights and 97% at 40-90m distance for load sign. The algorithm also achieves 46msec/frame processing time which also indicates the appropriateness of the algorithm in real-time processing.

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Image Retrieval System of semantic Inference using Objects in Images (이미지의 객체에 대한 의미 추론 이미지 검색 시스템)

  • Kim, Ji-Won;Kim, Chul-Won
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.7
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    • pp.677-684
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    • 2016
  • With the increase of multimedia information such as image, researches on extracting high-level semantic information from low-level visual information has been realized, and in order to automatically generate this kind of information. Various technologies have been developed. Generally, image retrieval is widely preceded by comparing colors and shapes among images. In some cases, images with similar color, shape and even meaning are hard to retrieve. In this article, in order to retrieve the object in an image, technical value of middle level is converted into meaning value of middle level. Furthermore, to enhance accuracy of segmentation, K-means algorithm is engaged to compute k values for various images. Thus, object retrieval can be achieved by segmented low-level feature and relationship of meaning is derived from ontology. The method mentioned in this paper is supposed to be an effective approach to retrieve images as required by users.

Implementation of a Single Human Detection Algorithm for Video Digital Door Lock (영상디지털도어록용 단일 사람 검출 알고리즘 구현)

  • Shin, Seung-Hwan;Lee, Sang-Rak;Choi, Han-Go
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.127-134
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    • 2012
  • Video digital door lock(VDDL) system detects people who access to the door and acquires the human image. Design considerations is that current consumption must be minimized by applying fast human detection algorithm because of battery-based operation. Since the digital door lock takes an image through a fixed camera, detection of a person based on background image leads to high degree of reliability. This paper deals with a single human detection algorithm suitable for VDDL with fulfilling these requirements such that it detects a moving object in an image, then identifies whether the object is a person or not using image processing. The proposed image processing algorithm consists of two steps: Firstly, it detects the human image region using both background image and skin color information. Secondly, it identifies the person using polar histogram based on proportional information of human body. Proposed algorithm is implemented in VDDL and is verified the performance through experiments.

Improved Real-Time Mean-Shift Face Tracking by Readjusting Detected Face Region Histogram (검출된 얼굴 영역 히스토그램 재조정을 통한 개선된 실시간 평균이동 얼굴 추적 방식)

  • Kim, Gui-sik;Lee, Jae-sung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.195-198
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    • 2013
  • Recognition and Tracking of interesting object is the significant field in Computer Vision. Mean-Shift algorithm have chronic problems that some errors are occurred when histogram of tracking area is similar to another area. in this paper, we propose to solve the problem. Each algorithm blocks skin color filtering, face detect and Mean-Shift started consecutive order assists better operation of the next algorithm. Avoid to operations of the overhead of tracking area similar to a histogram distribution areas overlap only consider the number of white pixels by running the Viola-Jones algorithm, simple arithmetic increases the convergence of the Mean-Shift. The experimental results, it comes to 78% or more of white pixels in the Mean-Shift search area, only if the recognition of the face area when it is configured to perform a Viola-Jones algorithm is tracking the object, was 100 percent successful.

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An Effective Shadow Elimination Method Using Adaptive Parameters Update (적응적 매개변수 갱신을 통한 효과적인 그림자 제거 기법)

  • Kim, Byeoung-Su;Lee, Gwang-Gook;Yoon, Ja-Young;Kim, Jae-Jun;Kim, Whoi-Yul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.11-19
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    • 2008
  • Background subtraction, which separates moving objects in video sequences, is an essential technology for object recognition and tracking. However, background subtraction methods are often confused by shadow regions and this misclassification of shadow regions disturbs further processes to perceive the shapes or exact positions of moving objects. This paper proposes a method for shadow elimination which is based on shadow modeling by color information and Bayesian classification framework. Also, because of dynamic update of modeling parametres, the proposed method is able to correspond adaptively to illumination changes. Experimental results proved that the proposed method can eliminate shadow regions effectively even for circumstances with varying lighting condition.

Changes of Physical and Chemical Properties for Making Raw Materials and Reproductions According to Manufacturing Stages in Traditional Korean White Porcelain

  • Kim, Du Hyeon;Jeong, Ji Youn;Oh, Eun Jeong;Han, Min Su
    • Journal of Conservation Science
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    • v.38 no.4
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    • pp.301-313
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    • 2022
  • We made a Korean white porcelain or Joseon Baekja jar and based on the raw materials used and reproductions of each stage, we aimed to compare and analyze the physicochemical changes of the raw materials such as clay at each manufacturing stage, as well as identify the characteristics and correlations. Although the basic main components of clay and glaze material are similar, their texture becomes denser in the process of bisque firing pottery (Chobeol-pyeon) and glaze firing pottery (Jaebeol-pyeon), and we confirmed that in addition to the tendency of increasing vitrification, low-temperature minerals such as mica and illite gradually disappeared, while high-temperature minerals such as cristobalite were newly created. This phenomenon has also been verified by the rapid decrease in absorption rate while the change in specific gravity was small. In addition, the color was greatly affected by the firing atmosphere, and the yellow-red chromaticity of the raw materials was higher during bisque firing but showed a rapidly decreasing characteristic during glaze firing. The value of magnetic susceptibility, which is related to iron (Fe) component, showed a tendency to decrease in glaze firing pottery. CT images were confirmed as a method that can indirectly estimate the change in the material properties of the object step-by-step for the entire object. In conclusion, the study of manufacturing stages of reproduction can provide basic data for scientific research on the estimation of porcelain and pottery making technology and changes in raw materials.

Evaluation of Robustness of Deep Learning-Based Object Detection Models for Invertebrate Grazers Detection and Monitoring (조식동물 탐지 및 모니터링을 위한 딥러닝 기반 객체 탐지 모델의 강인성 평가)

  • Suho Bak;Heung-Min Kim;Tak-Young Kim;Jae-Young Lim;Seon Woong Jang
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.297-309
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    • 2023
  • The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.

Design of Moving Picture Retrieval System using Scene Change Technique (장면 전환 기법을 이용한 동영상 검색 시스템 설계)

  • Kim, Jang-Hui;Kang, Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.3
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    • pp.8-15
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    • 2007
  • Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.