A new optical flow estimation method in joint EO/IR video surveillance

Hong Man; Robert J. Holt; Jing Wang; Rainer Martini; Ravi Netravali; Iraban Mukherjee

doi:10.1117/12.719164

30 April 2007 A new optical flow estimation method in joint EO/IR video surveillance

Hong Man, Robert J. Holt, Jing Wang, Rainer Martini, Ravi Netravali, Iraban Mukherjee

Proceedings Volume 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII; 65430P (2007) https://doi.org/10.1117/12.719164
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

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.

Citation Download Citation

Hong Man, Robert J. Holt, Jing Wang, Rainer Martini, Ravi Netravali, and Iraban Mukherjee "A new optical flow estimation method in joint EO/IR video surveillance", Proc. SPIE 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII, 65430P (30 April 2007); https://doi.org/10.1117/12.719164

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