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  • Open Access


    Depth Map Prediction of Occluded Objects Using Structure Tensor with Gain Regularization

    H. Shalma, P. Selvaraj*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1145-1161, 2023, DOI:10.32604/iasc.2023.036853

    Abstract The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images. A proposed approach of a modified semi-global block matching algorithm with variable window size and the gradient assessment of objects predicts the depth map. 3D modeling and view synthesis algorithms could effectively handle the obtained disparity maps. This work uses the consistency check method to find an accurate depth map for identifying occluded pixels. The prediction of the disparity map by semi-global block matching has used the benchmark dataset of Middlebury stereo for evaluation. The improved depth map quality within a… More >

  • Open Access


    An Intelligent Identification Approach of Assembly Interface for CAD Models

    Yigang Wang1, Hong Li1, Wanbin Pan1,*, Weijuan Cao1, Jie Miao1, Xiaofei Ai1, Enya Shen2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 859-878, 2023, DOI:10.32604/cmes.2023.027320

    Abstract Kinematic semantics is often an important content of a CAD model (it refers to a single part/solid model in this work) in many applications, but it is usually not the belonging of the model, especially for the one retrieved from a common database. Especially, the effective and automatic method to reconstruct the above information for a CAD model is still rare. To address this issue, this paper proposes a smart approach to identify each assembly interface on every CAD model since the assembly interface is the fundamental but key element of reconstructing kinematic semantics. First, as the geometry of an… More >

  • Open Access


    A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing

    Yanjun Zhang1, Yongqiang He2, Jingbo Zhang1, Yaru Zhao3, Zhihua Cui1,*, Wensheng Zhang4

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 363-383, 2023, DOI:10.32604/cmes.2023.025832

    Abstract The video compression sensing method based on multi hypothesis has attracted extensive attention in the research of video codec with limited resources. However, the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task. To resolve this problem, this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimization method. It mainly includes the optimization of prediction blocks (OPBS), the selection of search windows and the use of neighborhood information. Specifically, the OPBS consists of two parts: the selection of blocks and the optimization of prediction blocks. We combine the high-quality optimization reconstruction of… More >

  • Open Access


    Video Compressed Sensing Reconstruction Based on Multi-Dimensional Reference Frame Multi Hypothesis Rediction

    Hua Li1,*, Yuchen Yue2, Jianhua Luo3

    Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 61-68, 2022, DOI:10.32604/jihpp.2022.027692

    Abstract In this paper, a video compressed sensing reconstruction algorithm based on multidimensional reference frames is proposed using the sparse characteristics of video signals in different sparse representation domains. First, the overall structure of the proposed video compressed sensing algorithm is introduced in this paper. The paper adopts a multi-reference frame bidirectional prediction hypothesis optimization algorithm. Then, the paper proposes a reconstruction method for CS frames at the re-decoding end. In addition to using key frames of each GOP reconstructed in the time domain as reference frames for reconstructing CS frames, half-pixel reference frames and scaled reference frames in the pixel… More >

  • Open Access


    Artificial Intelligence-Based Image Reconstruction for Computed Tomography: A Survey

    Quan Yan1, Yunfan Ye1, Jing Xia1, Zhiping Cai1,*, Zhilin Wang2, Qiang Ni3

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2545-2558, 2023, DOI:10.32604/iasc.2023.029857

    Abstract Computed tomography has made significant advances since its introduction in the early 1970s, where researchers have mainly focused on the quality of image reconstruction in the early stage. However, radiation exposure poses a health risk, prompting the demand of the lowest possible dose when carrying out CT examinations. To acquire high-quality reconstruction images with low dose radiation, CT reconstruction techniques have evolved from conventional reconstruction such as analytical and iterative reconstruction, to reconstruction methods based on artificial intelligence (AI). All these efforts are devoted to constructing high-quality images using only low doses with fast reconstruction speed. In particular, conventional reconstruction… More >

  • Open Access


    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

    Sunyoung Bu1, Suwon Lee2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3083-3096, 2023, DOI:10.32604/cmes.2023.024460

    Abstract Reconstructing a three-dimensional (3D) environment is an indispensable technique to make augmented reality and augmented virtuality feasible. A Kinect device is an efficient tool for reconstructing 3D environments, and using multiple Kinect devices enables the enhancement of reconstruction density and expansion of virtual spaces. To employ multiple devices simultaneously, Kinect devices need to be calibrated with respect to each other. There are several schemes available that calibrate 3D images generated from multiple Kinect devices, including the marker detection method. In this study, we introduce a markerless calibration technique for Azure Kinect devices that avoids the drawbacks of marker detection, which… More > Graphic Abstract

    Easy to Calibrate: Marker-Less Calibration of Multiview Azure Kinect

  • Open Access


    Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

    Yuanyuan Wang1,*, Rui Wang2, Xiaofeng Ren3, Junan Lei2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1951-1972, 2023, DOI:10.32604/cmes.2023.026112

    Abstract The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function. To form dense mandatory constraints and improve matching accuracy, the traditional binocular reconstruction technology was improved threefold. First, a single moving laser line was introduced to carry out global scanning constraints on the target, which would well overcome the difficulty of installing and recognizing excessive laser lines. Second, four kinds of improved algorithms, namely, disparity replacement, superposition synthesis, subregion segmentation, and subregion segmentation centroid enhancement, were established based on different constraint mechanism. Last, the improved binocular reconstruction test device was developed to realize the dual… More >

  • Open Access


    A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

    Nihat Arslan1, Kali Gurkahraman2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 331-350, 2023, DOI:10.32604/cmc.2023.035087

    Abstract Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, including different translations, scales, and orientations, can be performed using these parametric curves. For this, Bézier and B-spline curves can be generated using a point set that belongs to the outer boundary of the object. The resulting object shape can be used in computer vision fields, such as searching and segmentation methods and training machine learning algorithms. The prerequisite for reconstructing the shape with parametric curves… More >

  • Open Access


    Thermal Properties Reconstruction and Temperature Fields in Asphalt Pavements: Inverse Problem and Optimisation Algorithms

    Zhonghai Jiang1, Qian Wang1, Liangbing Zhou2,*, Chun Xiao3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1693-1708, 2023, DOI:10.32604/fdmp.2023.025270

    Abstract A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two types of asphalt pavement materials… More >

  • Open Access


    3D Face Reconstruction from a Single Image Using a Combined PCA-LPP Method

    Jee-Sic Hur1, Hyeong-Geun Lee1, Shinjin Kang2, Yeo Chan Yoon3, Soo Kyun Kim1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6213-6227, 2023, DOI:10.32604/cmc.2023.035344

    Abstract In this paper, we proposed a combined PCA-LPP algorithm to improve 3D face reconstruction performance. Principal component analysis (PCA) is commonly used to compress images and extract features. One disadvantage of PCA is local feature loss. To address this, various studies have proposed combining a PCA-LPP-based algorithm with a locality preserving projection (LPP). However, the existing PCA-LPP method is unsuitable for 3D face reconstruction because it focuses on data classification and clustering. In the existing PCA-LPP, the adjacency graph, which primarily shows the connection relationships between data, is composed of the e-or k-nearest neighbor techniques. By contrast, in this study,… More >

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