Robust monocular SLAM in dynamic environments

• Published in: 2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) pp. 209 - 218
• Main Authors: Wei Tan, Haomin Liu, Zilong Dong, Guofeng Zhang, Hujun Bao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2013
• Subjects: and virtual realities; augmented; Cameras; Feature extraction; H.5.1 [Information Interfaces and Presentation]: Multimedia Information Systems-Artificial; I.4.8 [Image Processing and Computer Vision]: Scene Analysis-Tracking; Real-time systems; Robustness; Simultaneous localization and mapping; Solid modeling; Three-dimensional displays
• DOI: 10.1109/ISMAR.2013.6671781

We present a novel real-time monocular SLAM system which can robustly work in dynamic environments. Different to the traditional methods, our system allows parts of the scene to be dynamic or the whole scene to gradually change. The key contribution is that we propose a novel online keyframe representation and updating method to adaptively model the dynamic environments, where the appearance or structure changes can be effectively detected and handled. We reliably detect the changed features by projecting them from the keyframes to current frame for appearance and structure comparison. The appearance change due to occlusions also can be reliably detected and handled. The keyframes with large changed areas will be replaced by newly selected frames. In addition, we propose a novel prior-based adaptive RANSAC algorithm (PARSAC) to efficiently remove outliers even when the inlier ratio is rather low, so that the camera pose can be reliably estimated even in very challenging situations. Experimental results demonstrate that the proposed system can robustly work in dynamic environments and outperforms the state-of-the-art SLAM systems (e.g. PTAM).