From Event: SPIE Optical Engineering + Applications, 2017
A reliable approach for object segmentation based on template-matching filters is proposed. The system employs an adaptive strategy for the generation of space-variant filters which take into account several versions of the target and local statistical properties of the input scene. Moreover, the proposed method considers the geometric modifications of the target while is moving through a video sequence. The detection accuracy of the matched filter brings the location of the target of interest. The estimated location coordinates are used to compute the support area covered by the target using watershed segmentation technique. In each frame, the filter adapts according the geometrical changes of the target in order to estimate its current support region. Experimental tests carried out in a video sequence show that the proposed system yields a very good performance for accuracy detection, and object segmentation efficiency in real-life scenes.
Kenia Picos, Adán Hirales-Carbajal, and Victor H. Díaz-Ramírez, "Template-matched filtering for automatic object segmentation in real-life scenes," Proc. SPIE 10395, Optics and Photonics for Information Processing XI, 103950L (Presented at SPIE Optical Engineering + Applications: August 08, 2017; Published: 24 August 2017); https://doi.org/10.1117/12.2273563.
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