![]() Conversely, if you only want to run the motion segmentation, attach -skip_sfm to the command. If you have the prior information that the scene to be reconstructed is fully static, you can skip the motion segmentation module with -assume_static. The final results will be saved inside the image data folder with COLMAP output format. This will sequentially run optical flow -> point trajectory -> motion seg -> sfm. Python run_particlesfm.py -image_dir /path/to/the/image/folder/ \ ![]() If you are interested in potential collaboration or internship at ByteDance, please feel free to contact Hengkai Guo ( Installation In particular, for dynamic scenes, the acquired dense point trajectories can be fed into a specially designed trajectory-based motion segmentation module to select static point tracks, enabling the system to produce reliable camera trajectories on in-the-wild sequences with complex foreground motion.Ĭontact Wang Zhao ( Shaohui Liu ( and Hengkai Guo ( for questions, comments and reporting bugs. ![]() Inspired by Particle video, our method connects pairwise optical flows and optimizes dense point trajectories as long-range video correpondences, which are used in a customized global structure-from-motion framework with similarity averaging and global bundle adjustment. ![]() ParticleSfM is an offline structure-from-motion system for videos (image sequences). Code release for our ECCV 2022 paper "ParticleSfM: Exploiting Dense Point Trajectories for Localizing Moving Cameras in the Wild." by Wang Zhao, Shaohui Liu, Hengkai Guo, Wenping Wang and Yong-Jin Liu. ![]()
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