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 :
بازگشت