• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.859-871
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• 2013

In this paper, we propose an algorithm that generates multi-view images by grid-mesh based image domain warping using occlusion mask and various image features obtained from the stereoscopic images. In the proposed algorithm, we first extract image saliency map, line segments and disparity saliency map from stereo images and then get them through a process that improves the quality of extracted features. This process is accomplished in two steps. In the first step, reliability of disparity saliency map on object boundary regions is enhanced by using occlusion information. And in the second step, we enhance the quality of image features in terms of temporal consistency by using temporal consistency information for stereo images. With these enhanced features, multi-view images are generated by grid-mesh based image domain warping technique. Experimental results show that the proposed algorithm performs better than existing algorithms in terms of visual quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5506-5521
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• 2017

Three-dimensional video (3DV), as the new generation of video format standard, can provide the viewers with a vivid screen sense and a realistic stereo impression. Meanwhile the view synthesis has become an important issue for 3DV application. Differently from the conventional methods based on depth, in this paper we propose a new view synthesis algorithm, which can employ the correlation among views and warp in the image domain only. There are mainly two contributions. One is the incorporation of sobel edge points into feature extraction and matching, which can obtain a better stable homography and then a visual comfortable synthesis view compared to SIFT points only. The other is a novel image blending method proposed to obtain a better synthesis image. Experimental results demonstrate that the proposed method can improve the synthesis quality both in subjectivity and objectivity.

• Electronics and Telecommunications Trends
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• v.39 no.3
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• pp.107-115
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• 2024

Image synthesis has been remarkably developed in the computer vision domain and various researches have been proposed to generate realistic and high-resolution images. In particular, image-based virtual try-on is an application in fashion domain to simulate wearing clothes. Specifically, using input images of a fashion model and products, an realistic image of the model wearing the provided garments is synthesized. In this paper, we present a comprehensive review of technical trends in image-based virtual try-on technology. We first introduce relevant datasets and discuss their characteristics. Then, we categorize existing image synthesis methods into three main streams: warping-based methods, encoding-decoding-based methods, and diffusion-based methods. Finally, we explore other important research issues in the field of virtual try-on and analyze related researches aimed to tackling those challenges.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1175-1180
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• 1991

The purpose of this paper is to improve the matching accuracy in identifying corresponding points in the area-based matching for the processing of stereo vision. For the selection of window size, a new method is proposed based on frequency domain analysis. The effectiveness of the proposed method is confirmed through a series of experiments. To overcome disproportionate distortion in stereo image pair, a new matching method using the warped window is also proposed. In the algorithm, the window is warped according to imaging geometry. Experiments on a synthetic image show that the matching accuracy is improved by 14.1% and 4.2% over the rectangular window method and image warping method each.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.838-850
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• 2012

In this paper, we propose a novel algorithm that generates multi-view images by using various image features obtained from the given stereoscopic images. In the proposed algorithm, we first create an intensity gradient saliency map from the given stereo images. And then we calculate a block-based optical flow that represents the relative movement(disparity) of each block with certain size between left and right images. And we also obtain the disparities of feature points that are extracted by SIFT(scale-invariant We then create a disparity saliency map by combining these extracted disparity features. Disparity saliency map is refined through the occlusion detection and removal of false disparities. Thirdly, we extract straight line segments in order to minimize the distortion of straight lines during the image warping. Finally, we generate multi-view images by grid mesh-based image warping algorithm. Extracted image features are used as constraints during grid mesh-based image warping. The experimental results show that the proposed algorithm performs better than the conventional DIBR algorithm in terms of visual quality.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.265-274
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• 1999

In this paper, we propose a novel interframe coding algorithm especially appropriate for 3-D medical images. The proposed algorithm is based on a video coding algorithm using motion estimation/ compensation and transform coding. In the algorithm, warping is adopted lor motion compensation (MC). Then, by using adaptive mode selection, a motion compensated residual image and original image are mixed up in the wavelet transform domain for improvement in coding performance. The mixed image is then compressed by the zerotree coding method. We prove that the adaptive mode selection technique in the wavelet transform domain is very useful lor 3-D medical image coding. Simulation results show that the proposed scheme provides good performance regardless of inter-slice distance and is prospective for 3-D medical image compression.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.404-411
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• 2009

We introduce in this paper a new method for smooth foldover-free warping of images, based on the vector field deformation technique proposed by Von Funck et al. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of a point in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. From the user-specified constraints, it computes in the image domain a C1-continuous velocity vector field, along which each pixel progressively moves from its original position to the target. The target positions of the pixels are obtained by solving a set of partial derivative equations with the 4th order Runge-Kutta method. We show how our method can be useful for texture mapping with hard constraints. We start with an unconstrained planar embedding of a target mesh using a previously known method (Least Squares Conformal Map). Then, in order to obtain a texture map that satisfies the given constraints, we use the proposed warping method to align the features of the texture image with those on the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping, offers higher level of control for defining the constraints, and is simpler to implement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5978-5999
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• 2018

Pedestrian detection is a challenging area in the intelligent vehicles domain. During the last years, many works have been proposed to efficiently detect motion in images. However, the problem becomes more complex when it comes to detecting moving areas while the vehicle is also moving. This paper presents a variational optical flow-based method for motion estimation in vehicular traffic scenarios. We introduce a framework for detecting motion areas with small and large displacements by computing optical flow using a multilevel architecture. The flow field is estimated at the shortest level and then successively computed until the largest level. We include a filtering parameter and a warping process using bicubic interpolation to combine the intermediate flow fields computed at each level during optimization to gain better performance. Furthermore, we find that by including a penalization function, our system is able to effectively reduce the presence of outliers and deal with all expected circumstances in real scenes. Experimental results are performed on various image sequences from Daimler Pedestrian Dataset that includes urban traffic scenarios. Our evaluation demonstrates that despite the complexity of the evaluated scenes, the motion areas with both moving and static camera can be effectively identified.