Action Recognition Using Mined Hierarchical Compound Features

The field of Action Recognition has seen a large increase in activity in recent years. Much of the progress has been through incorporating ideas from single-frame object recognition and adapting them for temporal-based action recognition. Inspired by the success of interest points in the 2D spatial...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 33; no. 5; pp. 883 - 897
Main Authors:	Gilbert, A, Illingworth, J, Bowden, R
Format:	Journal Article
Language:	English
Published:	Los Alamitos, CA IEEE 01.05.2011 IEEE Computer Society The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Action recognition Algorithms Applied sciences Artificial intelligence Association rules Compounds Computer science; control theory; systems Data mining Data Mining - methods Data processing. List processing. Character string processing Databases, Factual Exact sciences and technology Feature extraction Hierarchies Humans Image Processing, Computer-Assisted - methods Itemsets learning Memory organisation. Data processing Movement - physiology Object recognition Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry real-time Recognition Searching Software spatiotemporal State of the art Three dimensional Two dimensional High performance Computer vision Action Data analysis High resolution Motion estimation Video signal Temporal databases learning Pattern recognition Data mining Real time Object recognition Optimization Action recognition Time resolution Discrimination real-time Behavioral analysis spatiotemporal Fires Classification Localization Spatial database
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!