Searching video for complex activities with finite state models

Date
2007-06
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Print ISSN
Electronic ISSN
Publisher
IEEE
Volume
Issue
Pages
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Series
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.

Course
Other identifiers
Book Title
Keywords
Computational methods, Discriminant analysis, Mathematical models, Query languages, Robust control, Three dimensional, Complex activities, Discriminative methods, Finite state models, Motion capture set, Motion estimation
Citation
Published Version (Please cite this version)