{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T05:29:58Z","timestamp":1667885398324},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"01","license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.aaai.org"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"<jats:p>With the increasing popularity of video content, automatic video understanding is becoming more and more important for streamlining video content consumption and reuse. In this work, we present TVAN\u2014temporal video analyzer\u2014a system for temporal video analysis aimed at enabling efficient and robust video description and search. Its main components include: temporal video segmentation, compact scene representation for efficient visual recognition, and concise scene description generation. We provide a technical overview of the system, as well as demonstrate its usefulness for the task of video search and navigation.<\/jats:p>","DOI":"10.1609\/aaai.v33i01.33019871","type":"journal-article","created":{"date-parts":[[2019,8,16]],"date-time":"2019-08-16T07:41:04Z","timestamp":1565941264000},"page":"9871-9872","source":"Crossref","is-referenced-by-count":0,"title":["Temporal Video Analyzer (TVAN): Efficient Temporal Video Analysis for Robust Video Description and Search"],"prefix":"10.1609","volume":"33","author":[{"given":"Daniel","family":"Rotman","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dror","family":"Porat","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yevgeny","family":"Burshtein","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Udi","family":"Barzelay","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"9382","published-online":{"date-parts":[[2019,7,17]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/5073\/4946","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/5073\/4946","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T06:36:10Z","timestamp":1667802970000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/5073"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,17]]},"references-count":0,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2019,7,23]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v33i01.33019871","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2019,7,17]]}}}