VIREO-374: LSCOM Semantic Concept Detectors Using Local Keypoint Features
نویسندگان
چکیده
Semantic concept detection aims to rank video shots in large scale video corpus according to the presence of a specific concept, such as ``sports'', ``charts'', ``people marching'', and etc. In recently years, mainly motivated by the NIST TRECVID [1] which provides common video data and benchmark evaluation, a number of successful concept detection systems have been developed. As manually annotation and evaluation of huge amount of semantic concepts is time-consuming, in TRECVID, each year only 10-20 semantic concepts were used for system comparison. Thanks to the effort of LSCOM [2], which have defined 1000+ semantic concepts and annotated 400+ of them on the development set of TRECVID-2005 corpus. Although the LSCOM annotation are publicly available, the detection of such a huge number of concepts is still difficult and time-consuming.
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