{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:22:00Z","timestamp":1781108520867,"version":"3.54.1"},"reference-count":25,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,10,1]]},"abstract":"<p>The advancement of multimedia technology has contributed to a large number of videos, so it is important to know how to retrieve information from video, especially for crime prevention and forensics. For the convenience of retrieving video data, content-based video retrieval (CBVR) has got great publicity. Aiming at improving the retrieval performance, we focus on the two key technologies: shot boundary detection and keyframe extraction. After being compared with pixel analysis and chi-square histogram, histogram-based method is chosen in this paper. Then we combine it with adaptive threshold method and use HSV color space to get the histogram. For keyframe extraction, four methods are analyzed and four evaluation criteria are summarized, both objective and subjective, so the opinion is finally given that different types of keyframe extraction methods can be used for varied types of videos. Then the retrieval can be based on keyframes, simplifying the process of video investigation, and helping criminal investigation personnel to improve work efficiency.<\/p>","DOI":"10.4018\/ijdcf.2017100102","type":"journal-article","created":{"date-parts":[[2017,8,15]],"date-time":"2017-08-15T11:54:40Z","timestamp":1502798080000},"page":"15-29","source":"Crossref","is-referenced-by-count":3,"title":["Performance Evaluation and Scheme Selection of Shot Boundary Detection and Keyframe Extraction in Content-Based Video Retrieval"],"prefix":"10.4018","volume":"9","author":[{"given":"Lingchen","family":"Gu","sequence":"first","affiliation":[{"name":"Shandong University, School of Information Science and Engineering, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ju","family":"Liu","sequence":"additional","affiliation":[{"name":"Shandong University, School of Information Science and Engineering, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aixi","family":"Qu","sequence":"additional","affiliation":[{"name":"Shandong University, School of Information Science and Engineering, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJDCF.2017100102-0","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477706"},{"key":"IJDCF.2017100102-1","author":"B. 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