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This paper demonstrates a new approach to detecting highlevel events that may be depicted in images or video frames. Given a non-annotated content item, a large number of previously trained visual concept detectors are applied to it and their responses are used for representing the content item with a model vector in a high-dimensional concept space. Subsequently, an improved subclass discriminant analysis method is used for identifying a concept subspace within the aforementioned conceptdoi:10.1145/1991996.1992064 dblp:conf/mir/TsampoulatidisGDMK11 fatcat:mkl2tj3s7bgoxjw4urjjtosila