Now showing items 1-6 of 6
Predicting Split Decisions in MPEG-2 to HEVC Video Transcoding
This paper proposes learning-based approaches for transcoding MPEG-2 video into HEVC. In the training mode of the transcoder, mappings between extracted features and split decisions are calculated. While in the transcoding ...
H.264/AVC to HEVC Video Transcoder Based on Dynamic Thresholding and Content Modeling
The new video coding standard, HEVC, was developed to succeed the current standard, H.264/AVC, as the state of the art in video compression. However, there is a lot of legacy content encoded with H.264/AVC. This paper ...
FPGA-Based Network Traffic Classification Using Machine Learning
(IEEE Xplore, 2020)
Real-time classification of internet traffic is critical for the efficient management of networks. Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. ...
A regression-based framework for estimating the objective quality of HEVC coding units and video frames
A no-reference objective quality estimation framework is proposed. The framework is suitable for any block-based video codec. In the proposed solution, features are extracted from coding units and summarized to form features ...
H.264/AVC Motion Vector Concealment Solutions Using Online and Offline Polynomial Regression
This paper introduces two polynomial regression solutions for error concealment by predicting the values of motion vectors of lost macroblocks. The two solutions are online and offline polynomial regression modeling. In ...
MPEG-2 to HEVC Video Transcoding With Content-Based Modeling
This paper proposes an efficient MPEG-2 to HEVC video transcoder. The objective of the transcoder is to migrate the abundant MPEG-2 video content to the emerging HEVC video coding standard. The transcoder introduces a ...