Shedding Light on People Action Recognition in Social Robotics by Means of Common Spatial Patterns

Shedding Light on People Action Recognition in Social Robotics by Means of Common Spatial Patterns

Blog Article

Action recognition in robotics is a research field that has gained momentum in recent years.In this work, a video activity recognition method is presented, which has the ultimate goal of endowing a robot with action recognition capabilities for a more natural social interaction.The application of Common Yoto Player Spatial Patterns (CSP), a signal processing approach widely used in electroencephalography (EEG), is presented in a novel manner to be used in activity recognition in videos taken by a humanoid robot.A sequence of skeleton data is considered as a multidimensional signal and filtered according to the CSP algorithm.Then, characteristics extracted from these filtered data are used as features for a classifier.

A database with 46 individuals performing six different actions has been created to test the proposed method.The CSP-based method along with a Linear Intermediate Discriminant Analysis (LDA) classifier has been compared to a Long Short-Term Memory (LSTM) neural network, showing that the former obtains similar or better results than the latter, while being simpler.