Paper
27 September 2016 A correlation-based algorithm for recognition and tracking of partially occluded objects
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Abstract
In this work, a correlation-based algorithm consisting of a set of adaptive filters for recognition of occluded objects in still and dynamic scenes in the presence of additive noise is proposed. The designed algorithm is adaptive to the input scene, which may contain different fragments of the target, false objects, and background to be rejected. The algorithm output is high correlation peaks corresponding to pieces of the target in scenes. The proposed algorithm uses a bank of composite optimum filters. The performance of the proposed algorithm for recognition partially occluded objects is compared with that of common algorithms in terms of objective metrics.
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Alexey Ruchay and Vitaly Kober "A correlation-based algorithm for recognition and tracking of partially occluded objects", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99712R (27 September 2016); https://doi.org/10.1117/12.2237335
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CITATIONS
Cited by 6 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Composites

Image filtering

Signal to noise ratio

Digital filtering

Electronic filtering

Target detection

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