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A gaussian groundplan projection area model for evolving probabilistic classifiers

Theodoridis, Theodoros and Agapitos, Alexandros and Hu, Huosheng (2011) A gaussian groundplan projection area model for evolving probabilistic classifiers. In: the 13th annual conference, 2011-07-12 - 2011-07-16.

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In this paper, an investigation of evolvable probabilistic classifiers is conducted, along with a thorough comparison between a classical Gaussian distance model, and the induction of Gaussian-to-circle projection model. The newly introduced model refers to a distance fitness measure, based on the projection of Gaussian distributions with geometric circles. The projection architecture aims to model and classify physical aggressive behaviours, by using biomechanical primitives. The primitives are being used to model the dynamics of the aggressive activities, by evolving biome-chanical classifiers, which can discriminate between three behaviours and six actions. Both evolutionary models have shown strong discrimination performances on recognising the individual actions of each behaviour. From the comparison, the proposed model outperformed the classical one with three ensemble programs. Copyright 2011 ACM.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Genetic and Evolutionary Computation Conference, GECCO'11
Uncontrolled Keywords: Action Recognition; Gaussian Fitness Model; Biomechanical Primitives; Time Series Classification
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 19 Jan 2015 14:37
Last Modified: 23 Sep 2022 18:44

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