Joint Dense 3D Interpretation and Multiple Motion Segmentation of Temporal Image Sequences: A Variational Framework with Active Curve Evolution and Level Sets (MP-S1)

Author(s) : Hicham Sekkati (INRS-EMT, Canada) Amar Mitiche (INRS-EMT, Canada)

Abstract : The aim of this study is to introduce a novel method for the simultaneous motion segmentation and dense 3D interpretation of temporal sequences of monocular images. The problem is to recover simultaneously 3D structure, 3D motion, and a motion-based segmentation from the image sequence spatio-temporal variations. Motion in space is considered relative to the viewing system so that both the viewing system and environmental objects are allowed to move. The problem is stated as a 3D motion segmentation problem with simultaneous depth estimation within the regions of segmentation. The Euler-Lagrange equations of minimization of the objective functional lead to curve evolution PDEs implemented via level sets.

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