Bertholet, Peter-Immanuel; Zwicker, Matthias (2016). Temporally Consistent Motion Segmentation from RGB-D Video Cornell University Library
1608.04642v1.pdf - Published Version
Available under License Publisher holds Copyright.
Download (6MB) | Preview
We present a method for temporally consistent motion segmentation from RGB-D videos assuming a piecewise rigid motion model. We formulate global energies over entire RGB-D sequences in terms of the segmentation of each frame into a number of objects, and the rigid motion of each object through the sequence. We develop a novel initialization procedure that clusters feature tracks obtained from the RGB data by leveraging the depth information.We minimize the energy using a coordinate descent approach that includes novel techniques to assemble object motion hypotheses. A main benefit of our approach is that it enables us to fuse consistently labeled object segments from all RGB-D frames of an input sequence into individual 3D object reconstructions.
|Item Type:||Report (Report)|
|Division/Institute:||08 Faculty of Science > Institute of Computer Science (INF) > Computer Graphics Group (CGG)
08 Faculty of Science > Institute of Computer Science (INF)
|UniBE Contributor:||Bertholet, Peter-Immanuel and Zwicker, Matthias|
|Subjects:||000 Computer science, knowledge & systems
500 Science > 510 Mathematics
|Publisher:||Cornell University Library|
|Date Deposited:||22 Aug 2016 10:58|
|Last Modified:||22 Aug 2016 10:58|