Type

Conference Proceedings

Authors

Noel E. O'Connor
Suzanne Little
Cem Direkoglu
Iveel Jargalsaikhan

Subjects

Computer Science

Topics
local descriptors pattern recognition human action recognition digital video state of the art multimedia systems information storage and retrieval systems support vector machine

An evaluation of local action descriptors for human action classification in the presence of occlusion (2014)

Abstract This paper examines the impact that the choice of local de- scriptor has on human action classifier performance in the presence of static occlusion. This question is important when applying human action classification to surveillance video that is noisy, crowded, complex and incomplete. In real-world scenarios, it is natural that a human can be occluded by an object while carrying out different actions. However, it is unclear how the performance of the proposed action descriptors are affected by the associated loss of information. In this paper, we evaluate and compare the classification performance of the state-of-art human local action descriptors in the presence of varying degrees of static occlusion. We consider four different local action descriptors: Trajectory (TRAJ), Histogram of Orientation Gradient (HOG), Histogram of Orientation Flow (HOF) and Motion Boundary Histogram (MBH). These descriptors are combined with a standard bag-of-features representation and a Support Vector Machine classifier for action recognition. We investigate the performance of these descriptors and their possible combinations with respect to varying amounts of artificial occlusion in the KTH action dataset. This preliminary investigation shows that MBH in combination with TRAJ has the best performance in the case of partial occlusion while TRAJ in combination with MBH achieves the best results in the presence of heavy occlusion.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> Subject = Computer Science: Information storage and retrieval systems
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Multimedia systems
Ireland -> Dublin City University -> Subject = Computer Science: Digital video
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Noel E. O'Connor, Suzanne Little, Cem Direkoglu, Iveel Jargalsaikhan

Experts in our system

1
Noel E. O'Connor
Dublin City University
Total Publications: 474
 
2
Suzanne Little
Dublin City University
Total Publications: 36
 
3
Cem Direkoglu
Dublin City University
Total Publications: 9
 
4
Iveel Jargalsaikhan
Dublin City University
Total Publications: 9