CoSLAM: Collaborative Visual SLAM in Dynamic Environments

By Danping Zou, Ping Tan. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013

375 citations recorded by the source corpus.

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Robust monocular SLAM in dynamic environments (2013, methodology): “In Zou and Tan [44]’s CoSLAM system, all cameras can move freely in the scene, where each camera works independently with intra-camera pose estimation, and both static and dynamic points are used to obtain inter-camera pose estimation for all cameras.”
Visual SLAM and Structure from Motion in Dynamic Environments (2018, background): “Tan et al. [152] also use a similar projection principle to detect dynamic features.”
A Survey on Aerial Swarm Robotics (2018, background): “Robots may also maintain the position uncertainty of each point in the map for handling of dynamic objects [190].”
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects (2018, neutral): “In the first case, a deformable world is assumed [12, 32, 53] and as-rigid-as-possible registration is performed, while in the second, rigid object instances are identified [40, 46] and tracked sparsely [48, 54] or densely [39].”