A novel approach for characterizing multimedia 3D video streams by means of quasiperiodic processes

This work proposes a novel methodology to describe the Low-Frequency behaviour of compressed 3D video streams, i.e., their average fluctuations on longer time scales. This study is innovative for two reasons. First, it proves that the LowFrequency behaviour of the video data belongs to the class of Quasi-Periodic processes. Second, it proposes an innovative approach to describe the long-term behaviour through a set of parameters directly derived from the Quasi-Periodic analysis. Reported results show that the proposed approach is effective in a wide variety of simulation scenarios. Furthermore, it can be easily generalized to other kinds of compressed two-dimensional (2D) streams, whatever the adopted algorithm, the compression degree, video resolution and format. This opens new unexplored possibilities in the field of 3D video characterization, identification and classification.