An adaptive approach for online segmentation of multi-dimensional mobile data
Tian Guo, Zhixian Yan, Karl Aberer · 2012
With increasing availability of mobile sensing devices including smartphones, online mobile data segmentation becomes an important topic in reconstructing and understanding mobile data. Traditional approaches like online time series segmentation either use a fixed model or only apply an adaptive model on one dimensional data; it turns out that such methods are not very applicable to build online segmentation for multiple dimensional mobile sensor data (e.g., 3D accelerometer or 11 dimension features like 'mean', 'variance', 'covariance', 'magnitude', etc).