Abstract
In this paper an approach for automatic target detection and tracking, using multisensor image sequences with the presence of camera motion is presented. The approach consists of three parts. The first part uses a motion segmentation method for the detection of targets in the visible images sequence. The second part uses a Gaussian background model for detecting objects presented in the infrared sequence, which is preprocessed to eliminate the camera motion. The third part combines the individual results of the detection systems; it extends the Joint Probabilistic Data Association (JPDA) algorithm to handle an arbitrary number of sensors. Our approach is tested using image sequences with high clutter on dynamic environments. Experimental results show that the system detects 99% of the targets in the scene, and the fusion module removes 90% of the false detections.
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© 2005 Springer-Verlag Berlin Heidelberg
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López-Gutiérrez, L., Altamirano-Robles, L. (2005). Decision Fusion for Target Detection Using Multi-spectral Image Sequences from Moving Cameras. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_88
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DOI: https://doi.org/10.1007/11492542_88
Publisher Name: Springer, Berlin, Heidelberg
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