A proposal for human action classification based on motion analysis and artificial neural networks
Thiago Rocha, Flávio de Barros Vidal, Alexandre Ricardo Soares Romariz · 2012
This paper describes the development and application of a method for human action recognition from motion analysis in a sequence of images using an artificial neural network. The proposed method is based on two stages: Computer Vision and Computational Intelligence. The Computer Vision stage is a combination of two motion analysis techniques: Histogram of Oriented Optical Flow and Object Contour Analysis. For the Computational Intelligence stage we use a Self-Organizing Map (SOM) optimized through Learning Vector Quantization (LVQ). The approach is then applied for classification of human actions in many real situations. Testing against a database with different kinds of human actions, we show the usefulness and robustness of this method, comparing it to other proposals in the literature.