Searching video for complex activities with finite state models
Author
İkizler, Nazlı
Forsyth, D.
Date
2007-06Source Title
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Publisher
IEEE
Language
English
Type
Conference PaperItem Usage Stats
138
views
views
122
downloads
downloads
Abstract
We 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.
Keywords
Computational methodsDiscriminant analysis
Mathematical models
Query languages
Robust control
Three dimensional
Complex activities
Discriminative methods
Finite state models
Motion capture set
Motion estimation