Digital video frame deletion tampering detection method based on deep neural network
The invention relates to a digital video frame deletion tampering detection method based on a deep neural network. The method comprises the following steps: editing a to-be-detected video into a plurality of video clips; extracting pixel-level differential features and global differential features o...
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| creator | WU TIANLE LIU XIAOLONG FENG DEWANG FENG CHUNHUI |
| description | The invention relates to a digital video frame deletion tampering detection method based on a deep neural network. The method comprises the following steps: editing a to-be-detected video into a plurality of video clips; extracting pixel-level differential features and global differential features of adjacent frames from the video clips by using a multi-scale differential convolutional neural network MsDCNN, and fusing the pixel-level differential features and the global differential features to form a multi-scale differential feature; inputting the multi-scale differential feature into an LSTM network using a one-way attention mechanism, obtaining network output scores of the video clips through a full connection layer, and determining whether frame deletion exists in intermediate pointsof the video clips or not; reducing false detection by using a post-processing method based on video local spatial-temporal features.
本发明涉及一种基于深度神经网络的数字视频删帧篡改检测方法。该方法实现过程：将待检测视频剪辑成为若干个视频片段；利用多尺度差分卷积网络MsDCNN从视频片段中提取相邻帧的像素级差分特征 |
| format | Patent |
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本发明涉及一种基于深度神经网络的数字视频删帧篡改检测方法。该方法实现过程：将待检测视频剪辑成为若干个视频片段；利用多尺度差分卷积网络MsDCNN从视频片段中提取相邻帧的像素级差分特征</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; PHYSICS ; PICTORIAL COMMUNICATION, e.g. TELEVISION</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210319&DB=EPODOC&CC=CN&NR=112532999A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210319&DB=EPODOC&CC=CN&NR=112532999A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WU TIANLE</creatorcontrib><creatorcontrib>LIU XIAOLONG</creatorcontrib><creatorcontrib>FENG DEWANG</creatorcontrib><creatorcontrib>FENG CHUNHUI</creatorcontrib><title>Digital video frame deletion tampering detection method based on deep neural network</title><description>The invention relates to a digital video frame deletion tampering detection method based on a deep neural network. The method comprises the following steps: editing a to-be-detected video into a plurality of video clips; extracting pixel-level differential features and global differential features of adjacent frames from the video clips by using a multi-scale differential convolutional neural network MsDCNN, and fusing the pixel-level differential features and the global differential features to form a multi-scale differential feature; inputting the multi-scale differential feature into an LSTM network using a one-way attention mechanism, obtaining network output scores of the video clips through a full connection layer, and determining whether frame deletion exists in intermediate pointsof the video clips or not; reducing false detection by using a post-processing method based on video local spatial-temporal features.
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本发明涉及一种基于深度神经网络的数字视频删帧篡改检测方法。该方法实现过程：将待检测视频剪辑成为若干个视频片段；利用多尺度差分卷积网络MsDCNN从视频片段中提取相邻帧的像素级差分特征</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY PHYSICS PICTORIAL COMMUNICATION, e.g. TELEVISION |
| title | Digital video frame deletion tampering detection method based on deep neural network |
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