View independent human gait recognition using markerless 3d human motion capture

Authors:
Tomasz Krzeszowski;Bogdan Kwolek;Agnieszka Michalczuk;Adam Świtoński;Henryk Josiński
Affiliations:
Rzeszow University of Technology, Rzeszów, Poland,Rzeszow University of Technology, Rzeszów, Poland;Rzeszow University of Technology, Rzeszów, Poland,Rzeszow University of Technology, Rzeszów, Poland;-;Silesian University of Technology, Gliwice, Poland;Silesian University of Technology, Gliwice, Poland
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

Citing 9
Cited 0

Using Gait as a Biometric, via Phase-weighted Magnitude Spectra

AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Learning Pedestrian Models for Silhouette Refinement

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
View-independent human motion classification using image-based reconstruction

Image and Vision Computing
Handbook of Remote Biometrics: for Surveillance and Security

Handbook of Remote Biometrics: for Surveillance and Security
HumanEva: Synchronized Video and Motion Capture Dataset and Baseline Algorithm for Evaluation of Articulated Human Motion

International Journal of Computer Vision
Action and gait recognition from recovered 3-D human joints

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
3D tracking for gait characterization and recognition

FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Swarm intelligence based searching schemes for articulated 3D body motion tracking

ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
MPCA: Multilinear Principal Component Analysis of Tensor Objects

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present an algorithm for view-independent human gait recognition. The human gait recognition is achieved using data obtained by our markerless 3D motion tracking algorithm. The tensorial gait data were reduced by multilinear principal component analysis and subsequently classified. The performance of the motion tracking algorithm was evaluated using ground-truth data from MoCap. The classification accuracy was determined using video sequences with walking performers. Experiments on multiview video sequences show the promising effectiveness of the proposed algorithm.