DocumentCode
596649
Title
Local spatio-temporal interest point detection for human action recognition
Author
Feng Li ; Jixiang Du
Author_Institution
Dept. of Comput. Sci. & Technol., Huaqiao Univ., Xiamen, China
fYear
2012
fDate
18-20 Oct. 2012
Firstpage
579
Lastpage
582
Abstract
This paper presents a unified action recognition framework combining harris3D descriptor with 3D SIFT detector. We perform action recognition experiments on the KTH dataset using Support Vector Machines. Experiments apply the leave-one-out and compare our proposed approach with state-of-the-art methods. The result shows that our proposed approach is effective. Compared with other approaches our approach is more robust, easier to compute.
Keywords
feature extraction; object recognition; spatiotemporal phenomena; support vector machines; 3D SIFT detector; KTH dataset; harris3D descriptor; human action recognition; spatiotemporal interest point detection; support vector machine; Computer vision; Computers; Conferences; Detectors; Educational institutions; Feature extraction; Humans;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4673-1743-6
Type
conf
DOI
10.1109/ICACI.2012.6463231
Filename
6463231
Link To Document