Detection and tracking of multiple targets in infrared images

Joao Dinis; Pedro Ribau; Bento A. Brazio Correia

doi:10.1117/12.352871

15 July 1999 Detection and tracking of multiple targets in infrared images

Joao Dinis, Pedro Ribau, Bento A. Brazio Correia

Proceedings Volume 3692, Acquisition, Tracking, and Pointing XIII; (1999) https://doi.org/10.1117/12.352871
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

Multitarget tracking in cluttered environments has to deal with noisy measurements from ambiguous origins, which leads to a process of hypotheses generation and evaluation in addition to the traditional estimation problem. The multiple hypothesis tracking (MHT) algorithm is a statistical data association that provides a high level of support for false alarms and temporary occlusion at the cost of high processing requirements. This paper describes a methodology developed for the detection of moving and stationary point targets that feeds the MHT based tracking algorithm implemented. The time filtering approach developed for target detection is based on a combined spatio-temporal analysis approach optimized for clutter driven situations. The analysis of the local variance behavior within a time window is followed by a spatial processing stage based on motion segmentation by region growing. Moving regions presenting similar properties are thus clustered into single entities. Furthermore, a background estimation algorithm is also used, aiming to increase the robustness of the detection method. Multitarget tracking is then achieved through a MHT methodology based on the spatial features of the segmented motion regions. Special attention is given to the evaluation of performance of the method in real IR image sequences.

Citation Download Citation

Joao Dinis, Pedro Ribau, and Bento A. Brazio Correia "Detection and tracking of multiple targets in infrared images", Proc. SPIE 3692, Acquisition, Tracking, and Pointing XIII, (15 July 1999); https://doi.org/10.1117/12.352871

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