• Title/Summary/Keyword: Video object segmentation

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Automatic Extraction of Focused Video Object from Low Depth-of-Field Image Sequences (낮은 피사계 심도의 동영상에서 포커스 된 비디오 객체의 자동 검출)

  • Park, Jung-Woo;Kim, Chang-Ick
    • Journal of KIISE:Software and Applications
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    • v.33 no.10
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    • pp.851-861
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    • 2006
  • The paper proposes a novel unsupervised video object segmentation algorithm for image sequences with low depth-of-field (DOF), which is a popular photographic technique enabling to represent the intention of photographer by giving a clear focus only on an object-of-interest (OOI). The proposed algorithm largely consists of two modules. The first module automatically extracts OOIs from the first frame by separating sharply focused OOIs from other out-of-focused foreground or background objects. The second module tracks OOIs for the rest of the video sequence, aimed at running the system in real-time, or at least, semi-real-time. The experimental results indicate that the proposed algorithm provides an effective tool, which can be a basis of applications, such as video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing systems.

A Robust Algorithm for Moving Object Segmentation and VOP Extraction in Video Sequences (비디오 시퀸스에서 움직임 객체 분할과 VOP 추출을 위한 강력한 알고리즘)

  • Kim, Jun-Ki;Lee, Ho-Suk
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.4
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    • pp.430-441
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    • 2002
  • Video object segmentation is an important component for object-based video coding scheme such as MPEG-4. In this paper, a robust algorithm for segmentation of moving objects in video sequences and VOP(Video Object Planes) extraction is presented. The points of this paper are detection, of an accurate object boundary by associating moving object edge with spatial object edge and generation of VOP. The algorithm begins with the difference between two successive frames. And after extracting difference image, the accurate moving object edge is produced by using the Canny algorithm and morphological operation. To enhance extracting performance, we app]y the morphological operation to extract more accurate VOP. To be specific, we apply morphological erosion operation to detect only accurate object edges. And moving object edges between two images are generated by adjusting the size of the edges. This paper presents a robust algorithm implementation for fast moving object detection by extracting accurate object boundaries in video sequences.

Video Object Segmentation Method Using Spatio-Temporal Information (시공간 정보를 이용한 동영상 객체 분할 기법)

  • Oh, Hyuk;Choi, Hwan-Soo;Jeong, Dong-Seok
    • Proceedings of the IEEK Conference
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    • pp.349-352
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    • 2000
  • 영상으로부터 의미있는 객체를 영역화하기 위하여, 움직임에 의한 시간적 정보를 이용하거나, 형태학적(Morphological) 기법과 같이 공간적 정보를 이용하는 방법이 있다. 그러나, 단지 시간적 정보나 공간적 정보만을 이용하는 방법은 그 한계를 가지고 있으며, 본 논문에서는 시공간 정보를 이용하여 분할하는 방법을 채택하였다. 시간적 분할에서는, 두 프레임에서 움직임 정보를 찾아내었던 기존 방법을 보완하여 연속되는 세 프레임을 사용하도록 하였다. 이렇게 하면 움직임이 미세한 영상에 대해서도 객체를 분리해 낼 가능성을 높일 수 있게 된다. 공간적 분할시에는, Watershed 알고리즘을 이용하는 형태학적 분할(Morphological Segmentation)[1][2]을 하게 되는데, 전처리 과정의 단일척도경사(Monoscale Gradient) 대신 다중척도 경사(Multiscale Gradient)[3][4]를 사용하여 미세한 경사는 누그러뜨리고 에지 부분의 경사만을 강조하게 하였다. 또한 개선된 Watershed 알고리즘을 제안하여 기존의 Watershed 알고리즘의 과분할 문제를 보완하였다.

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Weekly Supervised Video Object Segmentation based on Multiple Random Walker (약한 지도 학습의 다중 랜덤워크 기반 동영상 객체 분할)

  • Heo, Minhyeok;Lim, Kyungsun;Kim, Han-Ul;Koh, Yeong Jun;Kim, Chang-Su
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.147-148
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    • 2017
  • 본 논문에서는 간단한 사용자 입력과 다중 랜덤 워크(multiple random walker) 기법을 기반으로 동영상 내의 주요 객체를 분할하는 알고리즘을 제안한다. 우선 동영상의 첫 프레임에서 점 형태의 사용자의 입력을 받아 대략적인 객체와 배경의 위치를 얻고, Lab 색상의 측지거리를 이용하여 객체와 배경의 중요도 지도를 얻는다. 다음으로 영상을 슈퍼 픽셀 단위로 분할하고, 다중 랜덤 워크 기법을 적용하여 객체 분할을 수행한다. 랜덤 워크 기법 적용 시, 중요도 지도를 각 랜덤 워커의 초기 분포로 설정하고, 노드간 색상과 움직임 차이를 이용하여 전이 행렬을 계산한다. 마지막으로 결과를 정련한 뒤, 다음 프레임으로 분할 결과를 전파하여 시간적 일관성을 유지한다. 실험을 통하여 제안 기법이 기존 기법에 비하여 우수한 객체 분할 성능을 보임을 확인한다.

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A Study on Color Fuzzy Decision Algorithm in Video Object Segmentation

  • Byun, Oh-Sung;Moon, Sung-Ryong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.142-148
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    • 2004
  • In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

VLSI Architecture for Video Object Boundary Enhancement (비디오객체의 경계향상을 위한 VLSI 구조)

  • Kim, Jinsang-
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.11A
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    • pp.1098-1103
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    • 2005
  • The edge and contour information are very much appreciated by the human visual systems and are responsible for our perceptions and recognitions. Therefore, if edge information is integrated during extracting video objects, we can generate boundaries of oects closer to human visual systems for multimedia applications such as interaction between video objects, object-based coding, and representation. Most of object extraction methods are difficult to implement real-time systems due to their iterative and complex arithmetic operations. In this paper, we propose a VLSI architecture integrating edge information to extract video objects for precisely located object boundaries. The proposed architecture can be easily implemented into hardware due to simple arithmetic operations. Also, it can be applied to real-time object extraction for object-oriented multimedia applications.

A Study on Face Object Detection System using spatial color model (공간적 컬러 모델을 이용한 얼굴 객체 검출 시스템 연구)

  • Baek, Deok-Soo;Byun, Oh-Sung;Baek, Young-Hyun
    • 전자공학회논문지 IE
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    • v.43 no.2
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    • pp.30-38
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    • 2006
  • This paper is used the color space distribution HMMD model presented in MPEG-7 in order to segment and detect the wanted image parts as a real time without the user's manufacturing in the video object segmentation. Here, it is applied the wavelet morphology to remove a small part that is regarded as a noise in image and a part excepting for the face image. Also, it did the optimal composition by the rough set. In this paper, tile proposed video object detection algorithm is confirmed to be superior as detecting the face object exactly than the conventional algorithm by applying those to the different size images.put the of paper here.

Video Object Extraction Using Contour Information (윤곽선 정보를 이용한 동영상에서의 객체 추출)

  • Kim, Jae-Kwang;Lee, Jae-Ho;Kim, Chang-Ick
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.33-45
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    • 2011
  • In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

A Robust Object Extraction Method for Immersive Video Conferencing (몰입형 화상 회의를 위한 강건한 객체 추출 방법)

  • Ahn, Il-Koo;Oh, Dae-Young;Kim, Jae-Kwang;Kim, Chang-Ick
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.2
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    • pp.11-23
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    • 2011
  • In this paper, an accurate and fully automatic video object segmentation method is proposed for video conferencing systems in which the real-time performance is required. The proposed method consists of two steps: 1) accurate object extraction on the initial frame, 2) real-time object extraction from the next frame using the result of the first step. Object extraction on the initial frame starts with generating a cumulative edge map obtained from frame differences in the beginning. This is because we can estimate the initial shape of the foreground object from the cumulative motion. This estimated shape is used to assign the seeds for both object and background, which are needed for Graph-Cut segmentation. Once the foreground object is extracted by Graph-Cut segmentation, real-time object extraction is conducted using the extracted object and the double edge map obtained from the difference between two successive frames. Experimental results show that the proposed method is suitable for real-time processing even in VGA resolution videos contrary to previous methods, being a useful tool for immersive video conferencing systems.

Video object segmentation using a novel object boundary linking (새로운 객체 외곽선 연결 방법을 사용한 비디오 객체 분할)

  • Lee Ho-Suk
    • The KIPS Transactions:PartB
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    • v.13B no.3
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    • pp.255-274
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    • 2006
  • Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.