Human localization in video frames using a growing neural gas algorithm and fuzzy inference

• Published in: Kompʹûternaâ optika Vol. 41; no. 1; pp. 46 - 58
• Main Authors: Amosov, O., Ivanov, Y., Zhiganov, S.
• Format: Journal Article
• Language: English; Russian
• Published: 2017
• ISSN: 0134-2452; 2412-6179; 2412-6179
• DOI: 10.18287/2412-6179-2017-41-1-46-58

A problem of human body localization in video frames using growing neural gas and feature description based on the Histograms of Oriented Gradients is solved. The original neuro-fuzzy model of growing neural gas for reinforcement learning (GNG-FIS) is used as a basis of the algorithm. A modification of the GNG-FIS algorithm using a two-pass training with fuzzy remarking of classes and building of a heat map is also proposed. As follows from the experiments, the index of the correct localizations of the developed classifier from 90.5% to 93.2%, depending on the conditions of the scene, that allows the use of the algorithm in real systems of situational video analytics.