The algorithm of descriptor based on locality preserving projections

Zidonghua Xuebao/ Acta Automatica Sinica

Volumn 34, Issue 9, 2008, Pages 1174-1177

  Xu, Xiao Ming ^a   Yang, Dan ^a   Zhang, Xiao Hong ^a   Zhou, Xiao Long ^a  

^a CHONGQING UNIVERSITY   (China)

Author keywords

Descriptor; Feature point; Locality preserving projections (LPP); Principle component analysis (PCA)

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; GRADIENT METHODS;

DESCRIPTOR; FEATURE POINT; LOCALITY PRESERVING PROJECTIONS (LPP); PRINCIPLE COMPONENT ANALYSIS (PCA);

VECTORS;

EID: 53649086507     PISSN: 02544156     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1004.2008.01174     Document Type: Article

References (13)

1. Mikolajczyk K, Schmid C. A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10): 1615-1630.
2. Mikolajczyk K, Tuytelaars T, Schmid C, Zisserman A, Matas J, Schaffalitzky F. A comparison of affine region detectors. International Journal of Computer Vision, 2005, 65(1-2): 43-72.
3. Koenderink J, van Doorn A J. Representation of local geometry in the visual system. Biological Cybernetics, 1987, 55(6): 367-375.
4. Freeman W T, Adelson E H. The design and use of steerable filters. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(9): 891-906.
5. van Gool L J, Moons T, Ungureanu D. Affine/photometric invariants for planar intensity patterns. In: Proceedings of the 4th European Conference on Computer Vision. Cambridge, England: Springer, 1996. 642-651.
6. Belongie S, Malik J, Puzicha J. Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(4): 509-522.
7. Schaffalitzky F, Zisserman A. Multi-view matching for unordered image sets, or 'How do I organize my holiday snaps?'. In: Processing of the 7th European Conference on Computer Vision. Copenhagen, Denmark: Springer, 2002. 414-431.
8. Lowe D G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 2004, 60(2): 91-110.
9. Joliffe I T. Principal Component Analysis. London: Springer-Verlag, 2002.
10. Ye K, Sukthankar R. PCA-SIFT: a more distinctive representation for local image descriptors. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Washington D. C, USA: IEEE, 2004. 506-513.
11. He X F, Niyogi P. Locality Preserving Projections, Technical Report TR-2002-09, Computer Science Department, University of Chicago, USA, 2002.
12. Roweis S T, Saul L K. Nonlinear dimensionality reduction by locally linear embedding. Science, 290(5500): 2323-2326.
13. Belkin M, Niyogi P. Laplacian eigenmaps and spectral techniques for embedding and clustering. Advances in Neural Information Processing Systems 14. New York: Springer, 2002.