• Title/Summary/Keyword: feature reconstruction

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Face Image Compression Algorithm using Triangular Feature Extraction and GHA (삼각특징추출과 GHA를 이용한 얼굴영상 압축알고리즘)

  • Seo, Seok-Bae;Kim, Dae-Jin;Gang, Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.1
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    • pp.11-18
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    • 2001
  • In this paper, we proposed the image compression algorithm using triangular feature based GHA. In feature extraction, the input images are divided into eight areas of triangular shape, that has positional information for face image compression. The proposed algorithm reduces blocking effects in image reconstruction and contains informations of face feature and shapes of face as input images are divided into eight. We used triangular feature extraction for positional information and GHA for shape information of face images. Simulation results show that the proposed algorithm has a better performance than the block based K-means and non-parsed image based GHA in PSNR at the same bpp.

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Vision-based Obstacle Detection using Geometric Analysis (기하학적 해석을 이용한 비전 기반의 장애물 검출)

  • Lee Jong-Shill;Lee Eung-Hyuk;Kim In-Young;Kim Sun-I.
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.43 no.3 s.309
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    • pp.8-15
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    • 2006
  • Obstacle detection is an important task for many mobile robot applications. The methods using stereo vision and optical flow are computationally expensive. Therefore, this paper presents a vision-based obstacle detection method using only two view images. The method uses a single passive camera and odometry, performs in real-time. The proposed method is an obstacle detection method using 3D reconstruction from taro views. Processing begins with feature extraction for each input image using Dr. Lowe's SIFT(Scale Invariant Feature Transform) and establish the correspondence of features across input images. Using extrinsic camera rotation and translation matrix which is provided by odometry, we could calculate the 3D position of these corresponding points by triangulation. The results of triangulation are partial 3D reconstruction for obstacles. The proposed method has been tested successfully on an indoor mobile robot and is able to detect obstacles at 75msec.

Robust Real-Time Visual Odometry Estimation for 3D Scene Reconstruction (3차원 장면 복원을 위한 강건한 실시간 시각 주행 거리 측정)

  • Kim, Joo-Hee;Kim, In-Cheol
    • KIPS Transactions on Software and Data Engineering
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    • v.4 no.4
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    • pp.187-194
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    • 2015
  • In this paper, we present an effective visual odometry estimation system to track the real-time pose of a camera moving in 3D space. In order to meet the real-time requirement as well as to make full use of rich information from color and depth images, our system adopts a feature-based sparse odometry estimation method. After matching features extracted from across image frames, it repeats both the additional inlier set refinement and the motion refinement to get more accurate estimate of camera odometry. Moreover, even when the remaining inlier set is not sufficient, our system computes the final odometry estimate in proportion to the size of the inlier set, which improves the tracking success rate greatly. Through experiments with TUM benchmark datasets and implementation of the 3D scene reconstruction application, we confirmed the high performance of the proposed visual odometry estimation method.

Adaptively Compensated-Disparity Prediction Scheme for Stereo Image Compression and Reconstruction (스테레오 영상 압축 및 복원을 위한 적응적 변이보상 예측기법)

  • 배경훈;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.676-682
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    • 2002
  • In this paper, an effective stereo image compression and reconstruction technique using a new adaptively compensated-disparity prediction scheme is proposed. That is, by adaptively predicting the mutual correlation between the stereo image using the proposed method, the bandwidth of the stereo input image can be compressed to the level of the conventional 2D image and the predicted image also can be effectively reconstructed using this transmitted reference image and disparity data in the receiver. Especially, in the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the predicted image reconstruction is adaptively selected in accordance with the magnitude of this feature values. From this adaptive disparity estimation method, reduction of the mismatching probability of the disparity vectors is expected and as a result, the image quality in the reconstructed image can be improved. In addition, from some experiments using the CCETT's stereo images of 'Fichier', 'Manege' and 'Tunnel', it is shown that the proposed method improves the PSNR of the reconstructed image to about 9.08 dB on average by comparing with that of the conventional methods. And also, it is found that there is almost no difference between the original image and the predicted image reconstructed through the proposed method by comparison to that of the conventional methods.

3D Reconstruction and Self-calibration based on Binocular Stereo Vision (스테레오 영상을 이용한 자기보정 및 3차원 형상 구현)

  • Hou, Rongrong;Jeong, Kyung-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.9
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    • pp.3856-3863
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    • 2012
  • A 3D reconstruction technique from stereo images that requires minimal intervention from the user has been developed. The reconstruction problem consists of three steps of estimating specific geometry groups. The first step is estimating the epipolar geometry that exists between the stereo image pairs which includes feature matching in both images. The second is estimating the affine geometry, a process to find a special plane in the projective space by means of vanishing points. The third step, which includes camera self-calibration, is obtaining a metric geometry from which a 3D model of the scene could be obtained. The major advantage of this method is that the stereo images do not need to be calibrated for reconstruction. The results of camera calibration and reconstruction have shown the possibility of obtaining a 3D model directly from features in the images.

Reconstruction of Post Burn Ala Defect Using Adiposocutaneous Graft (지방피부복합조직 이식을 이용한 화상 후 콧방울 결손의 재건)

  • Kwon, Min-Joo;Lee, Jong-Wook;Koh, Jang-Hyu;Seo, Dong-Kook;Choi, Jai-Ku;Jang, Young-Chul
    • Archives of Plastic Surgery
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    • v.38 no.4
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    • pp.451-457
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    • 2011
  • Purpose: As a central feature of the face, the nose has considerable significance in appearance and expression. Reconstruction of full thickness defects of the nasal ala has always been a challenge because of the 3-dimensional structure. For reconstruction of post burn defects of ala, skin graft, local or pedicled flap and composite graft are optionally available. We have reconstructed the ala defects using adiposocutaneous graft and observed the outcome. Methods: From March 2003 to December 2010, 19 cases in 11 patients with scar contracture and defect on ala portion were performed operation using adiposocutaneous graft. As a donor site, we used the inguinal crease and posterior auricular area and the donor site was primarily closed. We made incision through the superior rim of ala and released fully. A graft is applied to recipient site with larger size than recipient volume. Results: The mean age of the patient was 38.6 years (16~51), males are seven patients and females are four patients. The operation was performed bilaterally in 5 patients and unilaterally in 6 patients. Composite grafts were harvested from inguinal area in 13 cases and posterior auricular area in 6 cases. In one case, we did 4 times of operation to get enough volume. All the grafts were well taken. The mean size of the graft was 3.63 $cm^2$. Conclusion: For reconstruction of post burn defects of ala, it's not easy to use local flap or pedicled flap because of hardness and fibrosis of surrounding tissue. So, we choose adiposocutaneous graft for ala deformity reconstruction, got satisfactory outcome in color matching and texture.

3D Feature Based Tracking using SVM

  • Kim, Se-Hoon;Choi, Seung-Joon;Kim, Sung-Jin;Won, Sang-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1458-1463
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    • 2004
  • Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

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Robust Features and Accurate Inliers Detection Framework: Application to Stereo Ego-motion Estimation

  • MIN, Haigen;ZHAO, Xiangmo;XU, Zhigang;ZHANG, Licheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.302-320
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    • 2017
  • In this paper, an innovative robust feature detection and matching strategy for visual odometry based on stereo image sequence is proposed. First, a sparse multiscale 2D local invariant feature detection and description algorithm AKAZE is adopted to extract the interest points. A robust feature matching strategy is introduced to match AKAZE descriptors. In order to remove the outliers which are mismatched features or on dynamic objects, an improved random sample consensus outlier rejection scheme is presented. Thus the proposed method can be applied to dynamic environment. Then, geometric constraints are incorporated into the motion estimation without time-consuming 3-dimensional scene reconstruction. Last, an iterated sigma point Kalman Filter is adopted to refine the motion results. The presented ego-motion scheme is applied to benchmark datasets and compared with state-of-the-art approaches with data captured on campus in a considerably cluttered environment, where the superiorities are proved.

Curvature Based ECG Signal Compression for Effective Communication on WPAN

  • Kim, Tae-Hun;Kim, Se-Yun;Kim, Jeong-Hong;Yun, Byoung-Ju;Park, Kil-Houm
    • Journal of Communications and Networks
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    • v.14 no.1
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    • pp.21-26
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    • 2012
  • As electrocardiogram (ECG) signals are generally sampled with a frequency of over 200 Hz, a method to compress diagnostic information without losing data is required to store and transmit them efficiently on a wireless personal area network (WPAN). In this paper, an ECG signal compression method for communications onWPAN, which uses feature points based on curvature, is proposed. The feature points of P, Q, R, S, and T waves, which are critical components of the ECG signal, have large curvature values compared to other vertexes. Thus, these vertexes were extracted with the proposed method, which uses local extrema of curvatures. Furthermore, in order to minimize reconstruction errors of the ECG signal, extra vertexes were added according to the iterative vertex selectionmethod. Through the experimental results on the ECG signals from Massachusetts Institute of Technology-Beth Israel hospital arrhythmia database, it was concluded that the vertexes selected by the proposed method preserved all feature points of the ECG signals. In addition, it was more efficient than the amplitude zone time epoch coding method.

Enhanced Reconstruction of Heavy Occluded Objects Using Estimation of Variance in Volumetric Integral Imaging (VII) (Volumetric 집적영상에서 분산 추정을 이용한 심하게 은폐된 물체의 향상된 복원)

  • Hwang, Yong-Seok;Kim, Eun-Soo
    • Korean Journal of Optics and Photonics
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    • v.19 no.6
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    • pp.389-393
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    • 2008
  • Enhanced reconstruction of heavy occluded objects was represented using estimation of variance in computational integral imaging. The system is analyzed to extract information of enhanced reconstruction from an elemental images set. To obtain elemental images with enhanced resolution, low focus error, and large depth of focus, synthetic aperture integral imaging (SAII) utilizing a digital camera has been adopted. The focused areas of the reconstructed image are varied with the distance of the reconstruction plane. When an occluded object is occluded heavily, an occluded object can not be reconstructed by removing the occluding object. To obtain reconstruction of the occluded object by remedying the effect of heavy occlusion, the statistical technique has been adopted.