Related papers: Objects Can Move: 3D Change Detection by Geometric Transformation Constistency

Objects Can Move: 3D Change Detection by Geometric Transformation Constistency

URL: http://arxiv.org/abs/2208.09870v1
Date: Sun, 21 Aug 2022 11:32:47 GMT
Title: Objects Can Move: 3D Change Detection by Geometric Transformation Constistency
Authors: Aikaterini Adam, Torsten Sattler, Konstantinos Karantzalos and Tomas Pajdla
Abstract summary: AR/VR applications and robots need to know when the scene has changed. We propose a 3D object discovery method that is based only on scene changes. Our method does not need to encode any assumptions about what is an object, but rather discovers objects by exploiting their coherent move.
Score: 32.07372152138814
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: AR/VR applications and robots need to know when the scene has changed. An example is when objects are moved, added, or removed from the scene. We propose a 3D object discovery method that is based only on scene changes. Our method does not need to encode any assumptions about what is an object, but rather discovers objects by exploiting their coherent move. Changes are initially detected as differences in the depth maps and segmented as objects if they undergo rigid motions. A graph cut optimization propagates the changing labels to geometrically consistent regions. Experiments show that our method achieves state-of-the-art performance on the 3RScan dataset against competitive baselines. The source code of our method can be found at https://github.com/katadam/ObjectsCanMove.

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