Abstract
High Efficiency Video Coding (HEVC) is a worldwide popular video coding standard due to its high coding efficiency. To make profits, forgers prefer to transcode videos from previous standards such as H.264/AVC to HEVC. To deal with this issue, an efficient method is proposed to expose such transcoded HEVC videos based on coding unit (CU) and prediction unit (PU) partition types. CU and PU partitioning are two unique syntactic units of HEVC that can reflect a video’s compression history. In this paper, CU and PU partition types of I pictures and P pictures are firstly extracted. Then, their mean frequencies are calculated and concatenated as distinguishing features, which are further sent to a support vector machine (SVM) for classification. Experimental results show that the proposed method can identify transcoded HEVC videos with high accuracy and has strong robustness against frame-deletion and shifted Group of Pictures (GOP) structure attacks.
Highlights
Owing to the rapid development of mobile web and video capture devices, people can shoot, transmit, and watch videos at any time and any place
Deleting particular pictures or objects, splicing different video sequences, which may lead to judicial misjudgment or fake news
An effective method is proposed to detect High Efficiency Video Coding (HEVC) videos transcoded from AVC videos
Summary
Owing to the rapid development of mobile web and video capture devices, people can shoot, transmit, and watch videos at any time and any place. 500 h worth of video content are uploaded to the video sharing website YouTube [1]. By using increasingly user-friendly video editing software, forgers can change the original video contents at will, such as inserting/. It is an essential thing to authenticate the credibility of a video. As we know, falsified videos must have encountered a re-encoding process because forgers have to decompress one video before tampering and recompress it after tampering [2], so re-encoding detection can be used as the first step when verifying the authentication of one given video, and it has become one of the most important video forensics techniques [3]. Numerous re-encoding detection methods have been proposed for videos recompressed with the same codec as the original one. Discrete cosine transform (DCT) coefficients [4]
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