Highly Influenced

# Non-negative matrix factorization framework for face recognition

@article{Wang2005NonnegativeMF, title={Non-negative matrix factorization framework for face recognition}, author={Yuan Wang and Yunde Jia and Changbo Hu and Matthew Turk}, journal={IJPRAI}, year={2005}, volume={19}, pages={495-511} }

- Published 2005 in IJPRAI
DOI:10.1142/S0218001405004198

Non-negative Matrix Factorization (NMF) is a part-based image representation method which adds a non-negativity constraint to matrix factorization. NMF is compatible with the intuitive notion of combining parts to form a whole face. In this paper, we propose a framework of face recognition by adding NMF constraint and classifier constraints to matrix factorization to get both intuitive features and good recognition results. Based on the framework, we present two novel subspace methods: Fisher… CONTINUE READING

Highly Cited

This paper has 127 citations. REVIEW CITATIONS

#### From This Paper

##### Figures, tables, and topics from this paper.

47 Citations

13 References

Similar Papers

#### Citations

##### Publications citing this paper.

#### Citation Statistics

#### 128 Citations

Citations per Year

Semantic Scholar estimates that this publication has

**128**citations based on the available data.See our **FAQ** for additional information.