Human re-identification system on highly parallel GPU and CPU architectures

Communications in Computer and Information Science

Volumn 149 CCIS, Issue , 2011, Pages 293-300

  Ba̧k, Sławomir ^a   Kurowski, Krzysztof ^b   Napierała, Krystyna ^c  

^a INRIA   (France)

^b POZNAN SUPERCOMPUTING AND NETWORKING CENTER   (Poland)

^c POZNAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Covariance Matrix; Generalized Eigenvalues; GPU; High Performance Computing; Re identification

Indexed keywords

COVARIANCE FEATURES; CPU ARCHITECTURE; EXPERIMENTAL EVALUATION; GENERALIZED EIGENVALUES; GPU; HIGH EFFICIENCY; HIGH PERFORMANCE COMPUTING; PARALLEL COMPUTING ARCHITECTURE; RE-IDENTIFICATION; REAL-TIME RESPONSE; RESPONSE TIME; VIDEO SURVEILLANCE SYSTEMS;

COMPUTER SOFTWARE SELECTION AND EVALUATION; COVARIANCE MATRIX; EIGENVALUES AND EIGENFUNCTIONS; MULTIMEDIA SYSTEMS; NETWORK SECURITY; PARALLEL ARCHITECTURES; SECURITY SYSTEMS;

MULTIMEDIA SERVICES;

EID: 79957960741     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-21512-4_35     Document Type: Conference Paper

References (10)

1. Bak, S., Corvee, E., Bremond, F., Thonnat, M.: Person re-identification using spatial covariance regions of human body parts. In: AVSS (2010)
2. Demmel, J.W., Heath, M.T.: Applied numerical linear algebra. In: Society for Industrial and Applied Mathematics. SIAM, Philadelphia (1997)
3. Förstner, W., Moonen, B.: A metric for covariance matrices. In: Quo vadis geodesia..? TR Dept. of Geodesy and Geoinformatics, Stuttgart University (1999)
4. Householder, A.S.: Unitary triangularization of a nonsymmetric matrix. Journal of the ACM 5 (1958)
5. Lessig, C.: Eigenvalue computation with CUDA. In: NVIDIA techreport (2007)
6. Poli, G., et al.: Processing neocognitron of face recognition on high performance environment based on GPU with CUDA architecture. In: SBAC-PAD, pp. 81-88. IEEE Computer Society, Los Alamitos (2008)
7. Sriram, V.: Design-space exploration of biologically-inspired visual object recognition algorithms using CPUs, GPUs, and FPGAs. In: MRSC (2010)
8. Tosato, D., Farenzena, M., Spera, M., Murino, V., Cristani, M.: Multi-class classification on riemannian manifolds for video surveillance. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6312, pp. 378-391. Springer, Heidelberg (2010)
9. Tuzel, O., Porikli, F., Meer, P.: Region covariance: A fast descriptor for detection and classification. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 589-600. Springer, Heidelberg (2006)
10. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: CVPR 2001, pp. 511-518 (2001)