Paper Info
Title
Three-dimensional action recognition using volume integrals
Abstract
This work proposes the volume integral (VI) as a new descriptor for three-dimensional action recognition. The descriptor transforms the actor's volumetric information into a two-dimensional representation by projecting the voxel data to a set of planes that maximize the discrimination of actions. Our descriptor significantly reduces the amount of data of the three-dimensional representations yet preserves the most important information. As a consequence, the action recognition process is greatly speeded up while achieving very high success rates. The method proposed is therefore especially appropriate for applications in which limitations of computing power and space are significant aspects to consider, such as real-time applications or mobile devices. Additionally, the descriptor is sensitive to reflected actions, i.e., same actions performed with different limbs can be differentiated. This paper tests the VI using several Dimensionality Reduction techniques (namely PCA, 2D-PCA, LDA) and different Machine Learning approaches (namely Clustering, SVM and HMM) so as to determine the best combination of these for the action recognition task. Experiments conducted on the public IXMAS dataset show that the VI compares favorably with state-of-the-art descriptors both in terms of classification rates and computing times.
Year
DOI
Venue
2012
10.1007/s10044-011-0239-5
Pattern Anal. Appl.
Keywords
Field
DocType
Action recognition,View invariance,Multi-camera,Motion descriptor
Voxel,Dimensionality reduction,Volume integral,Action recognition,Artificial intelligence,Cluster analysis,Computer vision,Pattern recognition,Support vector machine,Mobile device,Hidden Markov model,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
15
3
1433-7541
Citations 
PageRank 
References 
2
0.35
25
Authors
4
Name
Order
Citations
PageRank
Luis Díaz-Más120.35
Rafael Muñoz-Salinas235325.03
F. J. Madrid-Cuevas349825.10
R. Medina-Carnicer441724.80