Early detection of human actions—A hybrid approach |
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| Affiliation: | 1. Dpto. de Automatica y Computacion, Universidad Publica de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain;2. Institute of Smart Cities, Universidad Publica de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain;3. KERMIT, Dept. of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Coupure Links 653, 9000 Gent, Belgium;1. Informatics Center, Federal University of Pernambuco, Brazil;2. Department of Biomedical Engineering, Federal University of Pernambuco, Brazil;1. CONACYT Research Fellow – Centro de Investigación en Matemáticas (CIMAT), A.C., Jalisco S/N, Col. Valenciana, C.P. 36000 Guanajuato, Gto, Mexico;2. Centro de Investigación en Matemáticas (CIMAT), A.C., Jalisco S/N, Col. Valenciana, C.P. 36000 Guanajuato, Gto, Mexico;1. Department of Computer Science & Engineering, Dhaka University of Engineering & Technology, Gazipur, Bangladesh;2. Faculty of Engineering, Computing and Science, Swinburne University of Technology (Sarawak Campus), Malaysia;3. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia |
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| Abstract: | Early detection of human actions is essential in a wide spectrum of applications ranging from video surveillance to health-care. While human action recognition has been extensively studied, little attention is paid to the problem of detecting ongoing human action early, i.e. detecting an action as soon as it begins, but before it finishes. This study aims at training a detector to be capable of recognizing a human action when only partial action sample is seen. To do so, a hybrid technique is proposed in this work which combines the benefits of computer vision as well as fuzzy set theory based on the fuzzy Bandler and Kohout's sub-triangle product (BK subproduct). The novelty lies in the construction of a frame-by-frame membership function for each kind of possible movement. Detection is triggered when a pre-defined threshold is reached in a suitable way. Experimental results on a publicly available dataset demonstrate the benefits and effectiveness of the proposed method. |
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| Keywords: | Human action recognition Human activity recognition BK subproduct Human motion analysis |
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