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In the proposed hashing, a video is divided into some video groups. For each video group, a low-rank secondary frame is constructed from the low-rank component decomposed by applying tensor robust PCA to the video group. Since the low-rank component can well indicate spatial-temporal intrinsic structure of the video group and it is slightly disturbed by digital operations, feature extraction from the low-rank secondary frames is discriminative and stable. Next, spatial features and temporal features are extracted from low-rank secondary frames by Charlier moments and HOF, respectively. Since the Charlier moments are robust to geometric transform and they can efficiently distinguish video frames with different contents, the use of Charlier moments can make robust and discriminative spatial features. As the HOF can measure the distribution of motion information between frames, the temporal features formed by HOFs can provide good discrimination. Hash is ultimately determined by quantizing the spatial and temporal features and concatenating the quantized results. Numerous experiments on open video datasets indicate that the proposed hashing is superior to some hashing baseline schemes in terms of classification and copy detection.<\/jats:p>","DOI":"10.1093\/comjnl\/bxad130","type":"journal-article","created":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T05:24:18Z","timestamp":1704173058000},"page":"2162-2171","source":"Crossref","is-referenced-by-count":7,"title":["Video Hashing with Tensor Robust PCA and Histogram of Optical Flow for Copy Detection"],"prefix":"10.1093","volume":"67","author":[{"given":"Mengzhu","family":"Yu","sequence":"first","affiliation":[{"name":"Key Lab of Education Blockchain and Intelligent Technology , Ministry of Education, Guangxi Normal University, Guilin 541004 , China"},{"name":"Guangxi Key Lab of Multi-Source Information Mining & Security , Guangxi Normal University, Guilin 541004 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenjun","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Lab of Education Blockchain and Intelligent Technology , Ministry of Education, Guangxi Normal University, Guilin 541004 , China"},{"name":"Guangxi Key Lab of Multi-Source Information Mining & Security , Guangxi Normal University, Guilin 541004 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Lab of Education Blockchain and Intelligent Technology , Ministry of Education, Guangxi Normal University, Guilin 541004 , China"},{"name":"Guangxi Key Lab of Multi-Source Information Mining & Security , Guangxi Normal University, Guilin 541004 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoping","family":"Liang","sequence":"additional","affiliation":[{"name":"Key Lab of Education Blockchain and Intelligent Technology , Ministry of Education, Guangxi Normal University, Guilin 541004 , China"},{"name":"Guangxi Key Lab of Multi-Source Information Mining & Security , Guangxi Normal University, Guilin 541004 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianquan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Lab of Education Blockchain and Intelligent Technology , Ministry of Education, Guangxi Normal University, Guilin 541004 , China"},{"name":"Guangxi Key Lab of Multi-Source Information Mining & Security , Guangxi Normal University, Guilin 541004 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"2024062414154050000_ref1","doi-asserted-by":"crossref","first-page":"2741","DOI":"10.1093\/comjnl\/bxac115","article-title":"RTIM hashing: robust and compact video hashing with a rotation- and translation-invariant model","volume":"66","author":"Chen","year":"2023","journal-title":"J. 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