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Static and Dynamic Objects Analysis as a 3D Vector Field

Abstract : In the context of scene modelling, understanding, and landmark-based robot navigation, the knowledge of static scene parts and moving objects with their motion behaviours plays a vital role. We present a complete framework to detect and extract the moving objects to reconstruct a high quality static map. For a moving 3D camera setup, we propose a novel 3D Flow Field Analysis approach which accurately detects the moving objects using only 3D point cloud information. Further, we introduce a Sparse Flow Clustering approach to effectively and robustly group the motion flow vectors. Experiments show that the proposed Flow Field Analysis algorithm and Sparse Flow Clustering approach are highly effective for motion detection and seg-mentation, and yield high quality reconstructed static maps as well as rigidly moving objects of real-world scenarios.
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https://hal.archives-ouvertes.fr/hal-01584238
Contributor : Cansen Jiang <>
Submitted on : Friday, September 8, 2017 - 3:04:32 PM
Last modification on : Monday, March 30, 2020 - 8:42:36 AM

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  • HAL Id : hal-01584238, version 1

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Cansen Jiang, Pani Danda Paudel, Yohan Fougerolle, David Fofi, Cedric Demonceaux. Static and Dynamic Objects Analysis as a 3D Vector Field. International Conference on 3D Vision (3DV), Oct 2017, Qingdao, China. ⟨hal-01584238⟩

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