Electro-Optical (EO) and Infra-Red (IR) sensors have been jointly deployed in many surveillance systems. In this
work we study the special characteristics of optical flow in IR imagery, and introduce an optical flow estimation
method using co-registered EO and IR image frames. The basic optical flow calculation is based on the combined
local and global (CLG) method (Bruhn, Weickert and Schnorr, 2002), which seeks solutions that simultaneously
satisfy a local averaged brightness constancy constraint and a global flow smoothness constraint. While CLG
method can be directly applied to IR image frames, the estimated optical flow fields usually manifest high level
of random motions caused by thermal noise. Furthermore, IR sensors operating at different wavelengths, e.g.
meddle-wave infrared (MWIR) and long-wave infrared (LWIR), may yield inconsistent motions in optical flow
estimation. Because of the availability of both EO and IR sensors in many practical scenarios, we propose to
estimate optical flow jointly using both EO and IR image frames. This method is able to take advantage of the
complementary information offered by these two imaging modalities. The joint optical flow calculation fuses the
motion fields from EO and IR images using a cross-regularization mechanism and a non-linear flow fusion model
which aligns the estimated motions based on neighbor activities. Experiments performed on the OTCBVS
dataset demonstrated that the proposed approach can effectively eliminate many unimportant motions, and
significantly reduce erroneous motions, such as sensor noise.