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  • Open Access

    ARTICLE

    An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

    Jing Xin1,*, Kenan Du1, Jiale Feng1, Mao Shan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2621-2640, 2023, DOI:10.32604/cmes.2023.027467

    Abstract This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images. The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance. To address these issues, we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model. Then, an indoor RGB-D image semantic segmentation network is proposed, which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud model. Finally, Bayesian updating is… More >

  • Open Access

    ARTICLE

    Indoor Scene Splicing Based on Genetic Algorithm and ORB

    Tao Zhang1,*, Yi Cao2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1677-1685, 2022, DOI:10.32604/iasc.2022.027082

    Abstract The images generated by the image stitching algorithm have false shadow and poor real-time performance, and are difficult to maintain visual consistency. For this reason, a panoramic image stitching algorithm based on genetic algorithm is proposed. First, the oriented fast and rotated brief (ORB) algorithm is used to quickly perform detection and description of feature, then the initial feature point pairs are extracted according to the Euclidean distance for feature point rough matching, the parallelism of genetic algorithm is used to optimize the feature point matching performance. Finally, the PROSAC algorithm is used to remove mismatched point pairs and get… More >

  • Open Access

    ARTICLE

    Real-Time Dense Reconstruction of Indoor Scene

    Jinxing Niu1,*, Qingsheng Hu1, Yi Niu1, Tao Zhang1, Sunil Kumar Jha2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3713-3724, 2021, DOI:10.32604/cmc.2021.017418

    Abstract Real-time dense reconstruction of indoor scenes is of great research value for the application and development of service robots, augmented reality, cultural relics conservation and other fields. ORB-SLAM2 method is one of the excellent open source algorithms in visual SLAM system, which is often used in indoor scene reconstruction. However, it is time-consuming and can only build sparse scene map by using ORB features to solve camera pose. In view of the shortcomings of ORB-SLAM2 method, this article proposes an improved ORB-SLAM2 solution, which uses a direct method based on light intensity to solve the camera pose. It can greatly… More >

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