Open Access2D Information Space Based Action Recognition
Author(s) -
L. Aneesh Euprazia,
K. K. Thyagharajan
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a1060.1191s19
Subject(s) - artificial intelligence , convex hull , discriminative model , feature vector , pattern recognition (psychology) , computer science , computer vision , feature (linguistics) , action (physics) , space (punctuation) , solidity , object (grammar) , regular polygon , mathematics , quantum mechanics , programming language , linguistics , philosophy , physics , geometry , operating system
Video based human action recognition has attained more attraction from the researchers and it predominates in the field of computer vision and pattern recognition. In this paper we deliver a new approach to suppress the background data and to extract 2D data of foreground human object of the video sequence. A combination of convex hull area, convex hull perimeter, solidity and eccentricity is used to represent the feature vector. Experiments are conducted on Weizmann video dataset to assess how the system is doing. The discriminative nature of the feature vectors assures accuracy in action recognition.