İkizler, NazlıForsyth, D.2016-02-082016-02-082007-06http://hdl.handle.net/11693/27091Date of Conference: 17-22 June 2007Conference name: IEEE Conference on Computer Vision and Pattern Recognition, 2007We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach is based on units of activity at segments of the body, that can be composed across space and across the body to produce complex queries. The presence of search units is inferred automatically by tracking the body, lifting the tracks to 3D and comparing to models trained using motion capture data. We show results for a large range of queries applied to a collection of complex motion and activity. Our models of short time scale limb behaviour are built using labelled motion capture set. We compare with discriminative methods applied to tracker data; our method offers significantly improved performance. We show experimental evidence that our method is robust to view direction and is unaffected by the changes of clothing. © 2007 IEEE.EnglishComputational methodsDiscriminant analysisMathematical modelsQuery languagesRobust controlThree dimensionalComplex activitiesDiscriminative methodsFinite state modelsMotion capture setMotion estimationSearching video for complex activities with finite state modelsConference Paper10.1109/CVPR.2007.383168