Dynamic Object Detection and Tracking in Vision SLAM

[1] Kuai, Y., Wen, G., & Li, D. (2019). Masked and dynamic siamese network for robust visual tracking. Information Sciences, 503, 169-182. Search in Google Scholar

[2] Yang, D., Bi, S., Wang, W., Yuan, C., Wang, W., & Qi, X., et al. (2019). Dre-slam: dynamic rgb-d encoder slam for a differential-drive robot. Remote Sensing, 11(4). Search in Google Scholar

[3] Long, X., Zhang, W., & Zhao, B. (2020). Pspnet-slam: a semantic slam detect dynamic object by pyramid scene parsing network. IEEE Access, 8, 214685-214695. Search in Google Scholar

[4] Zhao, L., Liu, Z., Chen, J., Cai, W., & Zeng, L. (2019). A compatible framework for rgb-d slam in dynamic scenes. IEEE Access, PP(99), 1-1. Search in Google Scholar

[5] Liu, W., Mo, Y., Jiao, J., & Deng, Z. (2020). Ef-razor: an effective edge-feature processing method in visual slam. IEEE Access, PP(99), 1-1. Search in Google Scholar

[6] Guan, P., Cao, Z., Chen, E., Liang, S., & Yu, J. (2020). A real-time semantic visual slam approach with points and objects. International Journal of Advanced Robotic Systems, 17(1), 172988142090544. Search in Google Scholar

[7] Hempel, T., & Al-Hamadi, A. (2022). An online semantic mapping system for extending and enhancing visual slam. Engineering Applications of Artificial Intelligence, 111, 104830-. Search in Google Scholar

[8] Wang, R., Wan, W., Wang, Y., & Di, K. (2019). A new rgb-d slam method with moving object detection for dynamic indoor scenes. Remote Sensing, 11(10), 1143-. Search in Google Scholar

[9] Li, P., Yin, L., Gao, J., & Sun, Y. (2021). Semantic optimization of feature-based slam. Mathematical Problems in Engineering, 2021(4), 1-10. Search in Google Scholar

[10] Wen, W., Zhang, G., & Hsu, L. T. (2020). Object detection aided gnss and its integration with lidar in highly urbanized areas. IEEE Intelligent Transportation Systems Magazine, PP(99), XX5-XX5. Search in Google Scholar

[11] Wu, R., Pike, M., & Lee, B. G. (2021). Dt-slam: dynamic thresholding based corner point extraction in slam system. IEEE Access, PP(99), 1-1. Search in Google Scholar

[12] Sualeh, M., & Kim, G. W. (2020). Visual-lidar based 3d object detection and tracking for embedded systems. IEEE Access, PP(99), 1-1. Search in Google Scholar

[13] Dong, H., Weng, C. Y., Guo, C., Yu, H., & Chen, I. M. (2020). Real-time avoidance strategy of dynamic obstacles via half model-free detection and tracking with 2d lidar for mobile robots. IEEE/ASME Transactions on Mechatronics, PP(99), 1-1. Search in Google Scholar

[14] Cui, L., & Ma, C. (2020). Sdf-slam: semantic depth filter slam for dynamic environments. IEEE Access, PP(99), 1-1. Search in Google Scholar

[15] Li, G., Liao, X., Huang, H., Song, S., & Zeng, Y. (2021). Robust stereo visual slam for dynamic environments with moving object. IEEE Access, PP(99), 1-1. Search in Google Scholar

[16] Pancham, A., Withey, D., & Bright, G. (2020). Amore: cnn-based moving object detection and removal towards slam in dynamic environments. South African Journal of Industrial Engineering. Search in Google Scholar

[17] Saputra, M. R., Markham, A., & Trigoni, N. (2018). Visual slam and structure from motion in dynamic environments. ACM Computing Surveys (CSUR). Search in Google Scholar

[18] Jiao, J., Wang, C., Li, N., Deng, Z., & Xu, W. (2022). An adaptive visual dynamic-slam method based on fusing the semantic information. IEEE sensors journal. Search in Google Scholar

[19] Bescos, B., Cadena, C., & Neira, J. (2020). Empty cities: a dynamic-object-invariant space for visual slam. IEEE Transactions on Robotics, PP(99), 1-19. Search in Google Scholar

[20] Liu, S., Wang, Y., Dai, F., & Yu, J. (2019). Simultaneous 3d motion detection, long-term tracking and model reconstruction for multi-objects. International Journal of Humanoid Robotics, 16(04), 2255-2262. Search in Google Scholar

[21] Hong, S., Park, S. Y., Lee, S., Kim, J., & Park, J. I. (2021). Special issue on recent advancements in simultaneous localization and mapping (slam) and its applications. ETRI Journal, 43(4). Search in Google Scholar

[22] Zhai, Y., Lu, B., Li, W., & Ma, S. (2021). Jd-slam: joint camera pose estimation and moving object segmentation for simultaneous localization and mapping in dynamic scenes. International Journal of Advanced Robotic Systems. Search in Google Scholar

[23] Li, Y., Song, G., Hao, S., Mao, J., & Song, A. (2023). Semantic stereo visual slam toward outdoor dynamic environments based on orb-slam2. Industrial Robot. Search in Google Scholar

[24] Liu, Y., & Miura, J. (2021). Rdmo-slam: real-time visual slam for dynamic environments using semantic label prediction with optical flow. IEEE Access, PP(99), 1-1. Search in Google Scholar

[25] Hempel, T., & Al-Hamadi, A. (2020). Pixel-wise motion segmentation for slam in dynamic environments. IEEE Access, 08, 164521-164528. Search in Google Scholar