On robust optical flow estimation on image sequences with differently exposed frames using primal-dual optimization
Artikel i vetenskaplig tidskrift, 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



Tomas Bengtsson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Tomas McKelvey

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik

Konstantin Lindström

Volvo Cars

Image and Vision Computing

0262-8856 (ISSN)

Vol. 57 78-88


Elektroteknik och elektronik



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