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14 February 2015Generalization of the Viola-Jones method as a decision tree of strong classifiers for real-time object recognition in video stream
A. Minkina,1 D. Nikolaev,2 S. Usilin,3 V. Kozyrev1
1Visillect Service Ltd. (Russian Federation) 2Institute for Information Transmission Problems (Russian Federation) 3Institute for Systems Analysis (Russian Federation)
In this paper, we present a new modification of Viola-Jones complex classifiers. We describe a complex classifier in the form of a decision tree and provide a method of training for such classifiers. Performance impact of the tree structure is analyzed. Comparison is carried out of precision and performance of the presented method with that of the classical cascade. Various tree architectures are experimentally studied. The task of vehicle wheels detection on images obtained from an automatic vehicle classification system is taken as an example.
A. Minkina,D. Nikolaev,S. Usilin, andV. Kozyrev
"Generalization of the Viola-Jones method as a decision tree of strong classifiers for real-time object recognition in video stream", Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944517 (14 February 2015); https://doi.org/10.1117/12.2180941
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A. Minkina, D. Nikolaev, S. Usilin, V. Kozyrev, "Generalization of the Viola-Jones method as a decision tree of strong classifiers for real-time object recognition in video stream," Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 944517 (14 February 2015); https://doi.org/10.1117/12.2180941