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  • Open Access

    ARTICLE

    LiDAR-Visual SLAM with Integrated Semantic and Texture Information for Enhanced Ecological Monitoring Vehicle Localization

    Yiqing Lu1, Liutao Zhao2,*, Qiankun Zhao3

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1401-1416, 2025, DOI:10.32604/cmc.2024.058757 - 03 January 2025

    Abstract Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors. These vehicles are crucial in various fields, including environmental science research, ecological and environmental monitoring projects, disaster response, and emergency management. A key method employed in these vehicles for achieving high-precision positioning is LiDAR (lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping (SLAM). However, maintaining high-precision localization in complex scenarios, such as degraded environments or when dynamic objects are present, remains a significant challenge. To address this issue, we integrate both semantic and… More >

  • Open Access

    ARTICLE

    DKP-SLAM: A Visual SLAM for Dynamic Indoor Scenes Based on Object Detection and Region Probability

    Menglin Yin1, Yong Qin1,2,3,4,*, Jiansheng Peng1,2,3,4

    CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1329-1347, 2025, DOI:10.32604/cmc.2024.057460 - 03 January 2025

    Abstract In dynamic scenarios, visual simultaneous localization and mapping (SLAM) algorithms often incorrectly incorporate dynamic points during camera pose computation, leading to reduced accuracy and robustness. This paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic probability. Firstly, a parallel thread employs the YOLOX object detection model to gather 2D semantic information and compensate for missed detections. Next, an improved K-means++ clustering algorithm clusters bounding box regions, adaptively determining the threshold for extracting dynamic object contours as dynamic points change. This process divides the image into low dynamic, suspicious dynamic, and high More >

  • Open Access

    REVIEW

    Visual SLAM Based on Object Detection Network: A Review

    Jiansheng Peng1,2,*, Dunhua Chen1, Qing Yang1, Chengjun Yang2, Yong Xu2, Yong Qin2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3209-3236, 2023, DOI:10.32604/cmc.2023.041898 - 26 December 2023

    Abstract Visual simultaneous localization and mapping (SLAM) is crucial in robotics and autonomous driving. However, traditional visual SLAM faces challenges in dynamic environments. To address this issue, researchers have proposed semantic SLAM, which combines object detection, semantic segmentation, instance segmentation, and visual SLAM. Despite the growing body of literature on semantic SLAM, there is currently a lack of comprehensive research on the integration of object detection and visual SLAM. Therefore, this study aims to gather information from multiple databases and review relevant literature using specific keywords. It focuses on visual SLAM based on object detection, covering… More >

  • Open Access

    ARTICLE

    Feature Matching Combining Variable Velocity Model with Reverse Optical Flow

    Chang Zhao1, Wei Sun1,3,*, Xiaorui Zhang2,3, Xiaozheng He4, Jun Zuo1, Wei Zhao1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1083-1094, 2023, DOI:10.32604/csse.2023.032786 - 03 November 2022

    Abstract The ORB-SLAM2 based on the constant velocity model is difficult to determine the search window of the reprojection of map points when the objects are in variable velocity motion, which leads to a false matching, with an inaccurate pose estimation or failed tracking. To address the challenge above, a new method of feature point matching is proposed in this paper, which combines the variable velocity model with the reverse optical flow method. First, the constant velocity model is extended to a new variable velocity model, and the expanded variable velocity model is used to provide… More >

  • Open Access

    ARTICLE

    Monocular Visual SLAM for Markerless Tracking Algorithm to Augmented Reality

    Tingting Yang1,*, Shuwen Jia1, Ying Yu1, Zhiyong Sui2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1691-1704, 2023, DOI:10.32604/iasc.2023.027466 - 19 July 2022

    Abstract Augmented Reality (AR) tries to seamlessly integrate virtual content into the real world of the user. Ideally, the virtual content would behave exactly like real objects. This necessitates a correct and precise estimation of the user’s viewpoint (or that of a camera) with regard to the virtual content’s coordinate system. Therefore, the real-time establishment of 3-dimension (3D) maps in real scenes is particularly important for augmented reality technology. So in this paper, we integrate Simultaneous Localization and Mapping (SLAM) technology into augmented reality. Our research is to implement an augmented reality system without markers using… More >

  • Open Access

    ARTICLE

    A Map Construction Method Based on the Cognitive Mechanism of Rat Brain Hippocampus

    Naigong Yu*, Hejie Yu

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1147-1169, 2022, DOI:10.32604/cmes.2022.019430 - 14 March 2022

    Abstract The entorhinal-hippocampus structure in the mammalian brain is the core area for realizing spatial cognition. However, the visual perception and loop detection methods in the current biomimetic robot navigation model still rely on traditional visual SLAM schemes and lack the process of exploring and applying biological visual methods. Based on this, we propose a map construction method that mimics the entorhinal-hippocampal cognitive mechanism of the rat brain according to the response of entorhinal cortex neurons to eye saccades in recent related studies. That is, when mammals are free to watch the scene, the entorhinal cortex… More >

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