|
[1] Stein, G. P., Mano, O., & Shashua, A. (2003, June). Vision-based ACC with a single camera: bounds on range and range rate accuracy. In IEEE IV2003 intelligent vehicles symposium. Proceedings (Cat. No. 03TH8683) (pp. 120-125). IEEE.
[2] Gat, I., Benady, M., & Shashua, A. (2005). A monocular vision advance warning system for the automotive aftermarket. SAE transactions, 403-410.
[3] Dagan, E., Mano, O., Stein, G. P., & Shashua, A. (2004, June). Forward collision warning with a single camera. In IEEE Intelligent Vehicles Symposium, 2004 (pp. 37-42). IEEE.
[4] Kim, G., & Cho, J. S. (2012, October). Vision-based vehicle detection and inter-vehicle distance estimation. In 2012 12th International Conference on Control, Automation and Systems (pp. 625-629). IEEE.
[5] Li, B., Dai, Y., & He, M. (2018). Monocular depth estimation with hierarchical fusion of dilated cnns and soft-weighted-sum inference. Pattern Recognition, 83, 328-339.
[6] Fu, H., Gong, M., Wang, C., Batmanghelich, K., & Tao, D. (2018). Deep ordinal regression network for monocular depth estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2002-2011).
[7] Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014). Rich feature hierarchies for accurate object detection and semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 580-587).
[8] Girshick, R. (2015). Fast r-cnn. In Proceedings of the IEEE international conference on computer vision (pp. 1440-1448). [9] Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems, 28.
[10] He, K., Gkioxari, G., Dollár, P., & Girshick, R. (2017). Mask r-cnn. In Proceedings of the IEEE international conference on computer vision (pp. 2961-2969).
[11] Khoshelham, K., & Elberink, S. O. (2012). Accuracy and resolution of kinect depth data for indoor mapping applications. sensors, 12(2), 1437-1454.
[12] Hansard, M., Lee, S., Choi, O., & Horaud, R. P. (2012). Time-of-flight cameras: principles, methods and applications. Springer Science & Business Media.
[13] Fankhauser, P., Bloesch, M., Rodriguez, D., Kaestner, R., Hutter, M., & Siegwart, R. (2015, July). Kinect v2 for mobile robot navigation: Evaluation and modeling. In 2015 International Conference on Advanced Robotics (ICAR) (pp. 388-394). IEEE.
[14] Ranftl, R., Lasinger, K., Hafner, D., Schindler, K., & Koltun, V. (2020). Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer. IEEE transactions on pattern analysis and machine intelligence.
[15] Ji, Z., & Prokhorov, D. (2008, June). Radar-vision fusion for object classification. In 2008 11th International Conference on Information Fusion (pp. 1-7). IEEE.
[16] Xu, D., Anguelov, D., & Jain, A. (2018). Pointfusion: Deep sensor fusion for 3d bounding box estimation. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 244-253).
[17] Schumann, O., Hahn, M., Dickmann, J., & Wöhler, C. (2018, July). Semantic segmentation on radar point clouds. In 2018 21st International Conference on Information Fusion (FUSION) (pp. 2179-2186). IEEE.
[18] Nabati, R., & Qi, H. (2020). Radar-camera sensor fusion for joint object detection and distance estimation in autonomous vehicles. arXiv preprint arXiv:2009.08428. [19] Zhao, G., Xiao, X., Yuan, J., & Ng, G. W. (2014). Fusion of 3D-LIDAR and camera data for scene parsing. Journal of Visual Communication and Image Representation, 25(1), 165-183.
[20] Li, J., He, X., & Li, J. (2015, June). 2D LiDAR and camera fusion in 3D modeling of indoor environment. In 2015 National Aerospace and Electronics Conference (NAECON) (pp. 379-383). IEEE.
[21] Kumar, G. A., Lee, J. H., Hwang, J., Park, J., Youn, S. H., & Kwon, S. (2020). LiDAR and camera fusion approach for object distance estimation in self-driving vehicles. Symmetry, 12(2), 324.
[22] Dirgantara, F. M., Rohman, A. S., & Yulianti, L. (2019, September). Object Distance Measurement System Using Monocular Camera on Vehicle. In 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) (pp. 122-127). IEEE.
[23] Zaarane, A., Slimani, I., Al Okaishi, W., Atouf, I., & Hamdoun, A. (2020). Distance measurement system for autonomous vehicles using stereo camera. Array, 5, 100016.
[24] Salman, Y. D., Ku-Mahamud, K. R., & Kamioka, E. (2017, April). Distance measurement for self-driving cars using stereo camera. In International Conference on Computing and Informatics (Vol. 1, No. 105, pp. 235-242).
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