On robust optical flow estimation on image sequences with differently exposed frames using primal-dual optimization
Journal article, 2017

Optical flow methods are used to estimate pixelwise motion information based on consecutive frames in image sequences. The image sequences traditionally contain frames that are similarly exposed. However, many real-world scenes contain high dynamic range content that cannot be captured well with a single exposure setting. Such scenes result in certain image regions being over- or underexposed, which can negatively impact the quality of motion estimates in those regions. Motivated by this, we propose to capture high dynamic range scenes using different exposure settings every other frame. A framework for OF estimation on such image sequences is presented, that can straightforwardly integrate techniques from the state-of-the-art in conventional OF methods. Different aspects of robustness of OF methods are discussed, including estimation of large displacements and robustness to natural illumination changes that occur between the frames, and we demonstrate experimentally how to handle such challenging flow estimation scenarios. The flow estimation is formulated as an optimization problem whose solution is obtained using an efficient primal–dual method.

Temporal coherency

High dynamic range

Optical flow estimation

Primal–dual

Author

Tomas Bengtsson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Tomas McKelvey

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Konstantin Lindström

Volvo Cars

Image and Vision Computing

0262-8856 (ISSN)

Vol. 57 78-88

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1016/j.imavis.2016.11.003

More information

Latest update

6/15/2018