Sensory data in sequential format can be obtained from different sensors describing different events. As a clear example of their usability, a smartphone has several inbuilt sensors such as accelerometer, gyroscope, magnetometer, etc. Independently, each sensor continuously measures an action value (e.g. acceleration) at each time stamp. However, the interpretation of a series of instantaneous actions to higher-level events is complicated due to the lack of information in the one-dimensional series and the high similarity among different events. Inspired from image processing, sensory words are new descriptors of sequential data, where it captures the magnitude and orientation of data points and present them in frequency histogram. These words can be used afterwards as discriminative features to classify different types of sensory data.
08.11.2018 - 10:15