Gait analysis from encrypted video surveillance traffic

This thesis proposes an original video-based gait analysis technique, different from others existing in the literature. We leverage deep learning techniques to analyze video sequence packet size both in a virtual and real environment. Moreover, we address the case in which encryption mechanisms are adopted and we conclude the study proposing an incremental learning framework to render the system suitable to real life applications where training data becomes progressively available over time.ope

An Analysis of H.264/AVC Encryption Techniques

The video coding standards are developed to satisfy the requirements of different applications for various purposes, higher coding efficiency, better picture quality, and more error robustness. The new international video coding standard H.264/AVC aims at having significant improvements in coding efficiency, and error robustness in comparison with the previous standards. Most of the video compression algorithms are designed based on the H.264/AVC. In this paper, the video encryption techniques of H.264/AVC are analyzed. Performance analysis of the three algorithms namely Selective, Layered and NaEF;ve is reported and its strength is discussed