Visual SLAM in Dynamic Environments using Multi-lens Omnidirectional Camera
Visual SLAM in Dynamic Environments using Multi-lens Omnidirectional Camera
复制标题
使用多镜头全向相机的动态环境中的视觉 SLAM
DOI：
10.1109/lifetech53646.2022.9754868
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Shoya Yamasaki and Kousuke Matsushima
中科院分区：
文献类型：
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作者：
Kazuaki Sugai;Kohei Shirai;Kitahiro Kaneda;Keiichi Iwamura;Kohta Uematsu and Kousuke Matsushima;Reiya Murasaki and Kousuke Matsushima;Masahiro Yamawaki and Kousuke Matsushima;Shoya Yamasaki and Kousuke Matsushima
对于自动驾驶和辅助驾驶系统，已经进行了许多关于视觉SLAM(同时定位和映射)系统的研究。本文提出了一种多镜头全向摄像机与目标识别相结合的视觉SLAM系统。该方法可以有效地降低道路环境中车辆、行人、自行车等运动物体产生的噪声。通过改进跟踪线索，提出了一种稳健的抗跟踪丢失的SLAM系统。由于多镜头全向摄像机系统不仅可以看到场景的正面，而且可以看到场景的左右两侧，因此即使在纹理较少的场景中也可以获得有效的特征点。因此，它提供了比单目相机系统更好的SLAM结果。
Many studies relate to Visual SLAM (Simultaneous Localization and Mapping) systems have been conducted for automatic driving and assisted driving systems. In this paper, we propose the Visual SLAM system combining multi-lens omnidirectional camera and object recognition. The proposed method can reduce some noises caused by moving objects, such as vehicle, pedestrian, bicycle, and so on, in the road environment. We also propose a robust SLAM system against tracking loss by improving the tracking thread. Since a multi-lens omnidirectional camera system can view not only the front but also the left and right sides of the scene, it is possible to obtain effective feature points even in scenes with little texture. Therefore, it provides better SLAM results than monocular camera systems.