title: Event-Based 3D Motion Flow Estimation Using 4D Spatio Temporal Subspaces Properties.
abstract: State of the art scene flow estimation techniques are based on projections of the 3D motion on image using luminance-sampled at the frame rate of the cameras-as the principal source of information. We introduce in this paper a pure time based approach to estimate the flow from 3D point clouds primarily output by neuromorphic event-based stereo camera rigs, or by any existing 3D depth sensor even if it does not provide nor use luminance. This method formulates the scene flow problem by applying a local piecewise regularization of the scene flow. The formulation provides a unifying framework to estimate scene flow from synchronous and asynchronous 3D point clouds. It relies on the properties of 4D space time using a decomposition into its subspaces. This method naturally exploits the properties of the neuromorphic asynchronous event based vision sensors that allows continuous time 3D point clouds reconstruction. The approach can also handle the motion of deformable object. Experiments using different 3D sensors are presented.
authors.affiliation: Institut National de la Santé et de la Recherche Médicale, UMRI S 968; Sorbonne Université, University of Pierre and Marie Curie, Univ Paris 06, UMR S 968; Centre National de la Recherche Scientifique, UMR 7210, Institut de la Vision Paris, France.
authors.forename: Sio-Hoi
authors.initials: SH
authors.lastname: Ieng
authors.affiliation: Institut National de la Santé et de la Recherche Médicale, UMRI S 968; Sorbonne Université, University of Pierre and Marie Curie, Univ Paris 06, UMR S 968; Centre National de la Recherche Scientifique, UMR 7210, Institut de la Vision Paris, France.
authors.forename: João
authors.initials: J
authors.lastname: Carneiro
authors.affiliation: Institut National de la Santé et de la Recherche Médicale, UMRI S 968; Sorbonne Université, University of Pierre and Marie Curie, Univ Paris 06, UMR S 968; Centre National de la Recherche Scientifique, UMR 7210, Institut de la Vision Paris, France.
authors.forename: Ryad B
authors.initials: RB
authors.lastname: Benosman
keywords: 3D point clouds; event-based sensing; motion estimation; motion from structure; neuromorphic vision; scene flow