{"id":1274,"date":"2014-04-03T14:30:07","date_gmt":"2014-04-03T13:30:07","guid":{"rendered":"http:\/\/www.ceessnoek.info\/?p=1274"},"modified":"2014-04-03T14:30:07","modified_gmt":"2014-04-03T13:30:07","slug":"composite-concept-discovery-for-zero-shot-video-event-detection","status":"publish","type":"post","link":"https:\/\/www.ceessnoek.info\/index.php\/composite-concept-discovery-for-zero-shot-video-event-detection\/","title":{"rendered":"Composite Concept Discovery for Zero-Shot Video Event Detection"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1276\" alt=\"compositeconcepts\" src=\"http:\/\/www.ceessnoek.info\/wp-content\/uploads\/2014\/04\/compositeconcepts-e1396531760502.png\" width=\"400\" height=\"363\" align=\"right\" \/><\/p>\n<p>The ICMR2014 paper\u00a0<em>Composite Concept Discovery for Zero-Shot Video Event Detection<\/em> by <a href=\"http:\/\/staff.science.uva.nl\/~habibian\/\">Amirhossein Habibian<\/a>, Thomas Mensink and Cees Snoek is <a href=\"http:\/\/isis-data.science.uva.nl\/cgmsnoek\/pub\/habibian-composite-icmr14.pdf\">now available<\/a>. We consider automated detection of events in video without the use of any visual training examples. A common approach is to represent videos as classification scores obtained from a vocabulary of pre-trained concept classifiers. Where others construct the vocabulary by training individual concept classifiers, we propose to train classifiers for combination of concepts composed by Boolean logic operators. We call these concept combinations composite concepts and contribute an algorithm that automatically discovers them from existing video-level concept annotations. We discover composite concepts by jointly optimizing the accuracy of concept classifiers and their effectiveness for detecting events. We demonstrate that by combining concepts into composite concepts, we can train more accurate classifiers for the concept vocabulary, which leads to improved zero-shot event detection. Moreover, we demonstrate that by using different logic operators, namely \u201cAND\u201d, \u201cOR\u201d, we discover different types of composite concepts, which are complementary for zero-shot event detection. We perform a search for 20 events in 41K web videos from two test sets of the challenging TRECVID Multimedia Event Detection 2013 corpus. The experiments demonstrate the superior performance of the discovered composite concepts, compared to present-day alternatives, for zero-shot event detection.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The ICMR2014 paper\u00a0Composite Concept Discovery for Zero-Shot Video Event Detection by Amirhossein Habibian, Thomas Mensink and Cees Snoek is now available. We consider automated detection of events in video without the use of any visual training examples. A common approach is to represent videos as classification scores obtained from a vocabulary of pre-trained concept classifiers. [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-1274","post","type-post","status-publish","format-standard","hentry","category-science"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Composite Concept Discovery for Zero-Shot Video Event Detection - Cees Snoek<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ceessnoek.info\/index.php\/composite-concept-discovery-for-zero-shot-video-event-detection\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Composite Concept Discovery for Zero-Shot Video Event Detection - Cees Snoek\" \/>\n<meta property=\"og:description\" content=\"The ICMR2014 paper\u00a0Composite Concept Discovery for Zero-Shot Video Event Detection by Amirhossein Habibian, Thomas Mensink and Cees Snoek is now available. We consider automated detection of events in video without the use of any visual training examples. A common approach is to represent videos as classification scores obtained from a vocabulary of pre-trained concept classifiers. [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ceessnoek.info\/index.php\/composite-concept-discovery-for-zero-shot-video-event-detection\/\" \/>\n<meta property=\"og:site_name\" content=\"Cees Snoek\" \/>\n<meta property=\"article:published_time\" content=\"2014-04-03T13:30:07+00:00\" \/>\n<meta property=\"og:image\" content=\"http:\/\/www.ceessnoek.info\/wp-content\/uploads\/2014\/04\/compositeconcepts-e1396531760502.png\" \/>\n<meta name=\"author\" content=\"Cees\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Cees\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.ceessnoek.info\/index.php\/composite-concept-discovery-for-zero-shot-video-event-detection\/\",\"url\":\"https:\/\/www.ceessnoek.info\/index.php\/composite-concept-discovery-for-zero-shot-video-event-detection\/\",\"name\":\"Composite Concept Discovery for Zero-Shot Video Event Detection - 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