Savvas Argyropoulos

TL;DR: This paper proposes an innovative gait identification and authentication method based on the use of novel 2-D and 3-D features using the generalized radon transform, namely the radial integration transform and the circular integration transform.

TL;DR: This article reviews the different quality models that exploit packet- header-, bit stream-, or signal-information for providing audio, video, and audiovisual quality estimates, respectively and describes how these models can be applied for real-life monitoring, and how they can be adapted to reflect the information available at the given measurement point.

TL;DR: Simulations clearly demonstrate the superiority of the proposed method over other recent algorithms for transmission of H.264/AVC video streams over lossy packet networks.

TL;DR: A no-reference bit-stream based video quality assessment model that explicitly employs the predicted packet loss visibility estimates is presented and demonstrates that the use of continuous estimates for the visibility of packet losses improves the performance of the video quality Assessment model.

TL;DR: The proposed scheme exploits the error-resilient features of H.264/AVC codec and employs Reed-Solomon codes to protect effectively the streams and proposes a novel technique for adaptive classification of macroblocks into three slice groups.