title: Trends in correlation-based pattern recognition and tracking in forward-looking infrared imagery.
abstract: In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences.
authors: Department of Electrical and Computer Engineering, University of South, Alabama Mobile, AL 36688-0002, USA. malam@southalabama.edu.
authors: Mohammad S
authors: MS
authors: Alam
authors: Department of Electrical Engineering, Tuskegee University, Tuskegee, AL 36088, USA. bhuiyans@mytu.tuskegee.edu.
authors: Sharif M A
authors: SM
authors: Bhuiyan
mesh_terms: D001185:Artificial Intelligence; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D013055:Spectrophotometry, Infrared / Q000295:instrumentation* / Q000379:methods*; D013382:Subtraction Technique / Q000295:instrumentation