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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Advanced Computational Intelligence (ICACI), 2012 IEEE Fifth International Conference on
         
        
            Conference_Location : 
Nanjing
         
        
            Print_ISBN : 
978-1-4673-1743-6
         
        
        
            DOI : 
10.1109/ICACI.2012.6463231