• Title/Summary/Keyword: Shape-based Motion Estimation

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Contour Shape Matching based Motion Vector Estimation for Subfield Gray-scale Display Devices (서브필드계조방식 디스플레이 장치를 위한 컨투어 쉐이프 매칭 기반의 모션벡터 추정)

  • Choi, Im-Su;Kim, Jae-Hee
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.327-328
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    • 2007
  • A contour shape matching based pixel motion estimation is proposed. The pixel motion information is very useful to compensate the motion artifact generated at the specific gray level contours in the moving image for subfield gray-scale display devices. In this motion estimation method, the gray level boundary contours are extracted from the input image. Then using contour shape matching, the most similar contour in next frame is found, and the contour is divided into segment unit. The pixel motion vector is estimated from the displacement of the each segment in the contour by segment matching. From this method, more precise motion vector can be estimated and this method is more robust to image motion with rotation or from illumination variations.

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A Study on the Shape-Based Motion Estimation For MCFI (MCFI 구현을 위한 형태 기반 움직임 예측에 관한 연구)

  • Park, Ju-Hyun;Kim, Young-Chul;Hong, Sung-Hoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.3C
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    • pp.278-286
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    • 2010
  • Motion Compensated Frame Interpolation(MCFI) has been used to reduce motion jerkiness for dynamic scenes and motion blurriness for LCD-panel display as post processing for large screen and full HD(high definition) display. Conventionally, block matching algorithms (BMA) are widely used to do motion estimation for simplicity of implementation. However, there are still several drawbacks. So in this paper, we propose a novel shape-based ME algorithm to increase accuracy and reduce ME computational cost. To increase ME accuracy, we do motion estimation based on shape of moving objects. And only moving areas are included for motion estimation to reduce computational cost. The results show that the computational cost is 25 % lower than full search BMA, while the performance is similar or is better, especially in the fast moving region.

Motion Estimation using new blocks based on the Frame Difference for Frame Rate-up Conversion

  • Kwak, Tong-Ill;Yun, Jong-Ho;Cho, Hwa-Hyun;Choi, Myung-Ryul
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.1043-1046
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    • 2008
  • In this paper, we propose a Motion Estimation (ME) using new blocks based on the Frame Difference (FD) between two adjacent frames for Frame Rate-up Conversion (FRC). The proposed algorithm decides the shape of blocks by the FD. The experimental results show that the proposed method has better performance than conventional methods.

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Occluded Object Motion Estimation System based on Particle Filter with 3D Reconstruction

  • Ko, Kwang-Eun;Park, Jun-Heong;Park, Seung-Min;Kim, Jun-Yeup;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.60-65
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    • 2012
  • This paper presents a method for occluded object based motion estimation and tracking system in dynamic image sequences using particle filter with 3D reconstruction. A unique characteristic of this study is its ability to cope with partial occlusion based continuous motion estimation using particle filter inspired from the mirror neuron system in human brain. To update a prior knowledge about the shape or motion of objects, firstly, fundamental 3D reconstruction based occlusion tracing method is applied and object landmarks are determined. And optical flow based motion vector is estimated from the movement of the landmarks. When arbitrary partial occlusions are occurred, the continuous motion of the hidden parts of object can be estimated by particle filter with optical flow. The resistance of the resulting estimation to partial occlusions enables the more accurate detection and handling of more severe occlusions.

A Defocus Technique based Depth from Lens Translation using Sequential SVD Factorization

  • Kim, Jong-Il;Ahn, Hyun-Sik;Jeong, Gu-Min;Kim, Do-Hyun
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.383-388
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    • 2005
  • Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

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The motion estimation algorithm implemented by the color / shape information of the object in the real-time image (실시간 영상에서 물체의 색/모양 정보를 이용한 움직임 검출 알고리즘 구현)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2733-2737
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    • 2014
  • Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

A study of a motion estimation with the block-based method (Block-Based Method를 이용한 Motion Estimation에 관한 연구)

  • 김상기;이원희;김재영;변재응;이범로;정진현
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1-4
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    • 1996
  • It is difficult that a non-translational motion in a block is estimated by the block matching algorithm (BMA). In this paper, a nodal-displacement-based deformation model is used for this reason. This model assumes that a selected number of control nodes move freely in a block and that displacement of any interior point can be interpolated from nodal displacements. As a special case with a single node this model is equivalent to a translational model. And this model can represent more complex deformation using more nodes. We used an iterative gradient based search algorithm to estimate nodal displacement. Each iteration involves the solution of a simple linear equation. This method is called the deformable block matching algorithm (DBMA).

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Analysis of MPEG-4 Encoder for Object-based Video (실시간 객체기반 비디오 서비스를 위한 MPEG-4 Encoder 분석)

  • Kim Min Hoon;Jang Euee Seon;Lee Sun young;Moon Seok ju
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.1
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    • pp.13-20
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    • 2004
  • In this paper, we have analyzed the current MPEG-4 video encoding tools and proposed efcient coding techniques that reduce the complexity of the encoder. Until recently, encoder optimization without shape coding has been a major concern in video for wire/wireless low bit rate coding services. Recently, we found out that the computational complexity of MPEG-4 shape coding plays a very important role in the object-based coding through experiments. We have made an experiment whether we could get optimized object-based coding method through successfully combining latest optimized texture coding techniques with our proposed optimized shape coding techniques. In texture coding, we applied the MVFAST method for motion estimation. We chose not to use IVOPF(Intelligent VOP Formation) but to use TRB(Tightest Rectangular Boundary) for positioning VOP and, finally, to eliminate the spiral search of shape motion estimation to reduce the complexity in shape coding. As a result of experiment, our proposed scheme achieved improved time complexity over the existing reference software by $57.3\%$ and over the optimized method on which only shape coding was applied by $48.7\%$, respectively.

Very Low Bit Rate Video Coding Algorithm Using Uncovered Region Prediction (드러난 영역 예측을 이용한 초저 비트율 동영상 부호화)

  • 정영안;한성현;최종수;정차근
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.4
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    • pp.771-781
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    • 1997
  • In order to solve the problem of uncovered background region due to the region-due to the region-based motion estimation, this paper presents a new method which generates the uncovered region memory using motion estimation and shows the application of the algorithm for very low bit rate video coding. The proposed algorithm can be briefly described as follows it detects the changed region by using the information of FD(frame difference) and segmentation, and then as for only that region the backward motion estimation without transmission of shape information is done. Therefore, from only motion information the uncovered background region memory is generated and updated. The contents stored in the uncovered background region memory are referred whenever the uncovered region comes into existence. The regions with large prediction error are transformed and coded by using DCT. As results of simulation, the proposed algorithm shows the superior improvement in the subjective and objective image quality due to the remarkable reduction of transmission bits for prediction error.

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NATURAL INTERACTION WITH VIRTUAL PET ON YOUR PALM

  • Choi, Jun-Yeong;Han, Jae-Hyek;Seo, Byung-Kuk;Park, Han-Hoon;Park, Jong-Il
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.341-345
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    • 2009
  • We present an augmented reality (AR) application for cell phone where users put a virtual pet on their palms and play/interact with the pet by moving their hands and fingers naturally. The application is fundamentally based on hand/palm pose recognition and finger motion estimation, which is the main concern in this paper. We propose a fast and efficient hand/palm pose recognition method which uses natural features (e.g. direction, width, contour shape of hand region) extracted from a hand image with prior knowledge for hand shape or geometry (e.g. its approximated shape when a palm is open, length ratio between palm width and pal height). We also propose a natural interaction method which recognizes natural motion of fingers such as opening/closing palm based on fingertip tracking. Based on the proposed methods, we developed and tested the AR application on an ultra-mobile PC (UMPC).

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