Variational Temporal Optical Flow for Multi-exposure Video

High Dynamic Range (HDR) reconstruction for multi-exposure video sequences is a very challenging task. One of its main steps is registration of input frames. We propose a novel variational model for optical flow estimation for multi-exposure video sequences. We introduce data terms for consecutive and non consecutive frames, the latter term comparing frames with the same exposure. We also compute forward and backward flow terms for the current frame, naturally introducing temporal regularization. We present a particular formulation with sequences with two exposures, that can be extended to larger number of exposures. We compare the proposed method with state of the art variational models.