Compressive sensing based face detection without explicit image reconstruction using support vector machines

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7950 LNCS, Issue , 2013, Pages 758-765

  Magalhães, Filipe ^a,b   Sousa, Ricardo ^b   Araújo, Francisco M ^a   Correia, Miguel V ^a,b  

^a UNIVERSITY OF PORTO   (Portugal)

^b UNIVERSITY OF PORTO   (Portugal)

Author keywords

Compressive Sensing; Face Detection; Feature Selection; Pattern Recognition

Indexed keywords

COMPARATIVE EXPERIMENTS; COMPRESSIVE SENSING; HUMAN FACES; SIFT DESCRIPTOR;

FACE RECOGNITION; FEATURE EXTRACTION; IMAGE ANALYSIS; PATTERN RECOGNITION;

IMAGE RECONSTRUCTION;

EID: 84884474932     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-39094-4_87     Document Type: Conference Paper

References (15)

1. Candes, E., Tao, T.: Decoding by linear programming. IEEE Transactions on Information Theory 51(12), 4203-4215 (2005)
2. Candès, E.J., Tao, T.: Near-optimal signal recovery from random projections: Universal encoding strategies? IEEE Transactions on Information Theory 52(12), 5406-5425 (2006)
3. Donoho, D.L.: Compressed sensing. IEEE Trans. Inform. Theory 52, 1289-1306 (2006)
4. Duarte, M., Davenport, M., Wakin, M., Baraniuk, R.: Sparse signal detection from incoherent projections. In: Proceedings of 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006, vol. 3, p. III (2006)
5. Duarte, M., Sarvotham, S., Baron, D., Wakin, M., Baraniuk, R.: Distributed compressed sensing of jointly sparse signals. In: Conference Record of the Thirty-Ninth Asilomar Conference on Signals, Systems and Computers, pp. 1537-1541 (2005)
6. Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories. Comput. Vis. Image Underst. 106(1), 59-70 (2007), http://dx.doi.org/10.1016/j.cviu.2005.09.012
7. Geng, C., Jiang, X.: Face recognition using SIFT features. In: Proceedings of the 16th IEEE International Conference on Image Processing, ICIP 2009, pp. 3277-3280. IEEE Press, Piscataway (2009)
8. Junior, L., Thomaz, C.: Fei face database (2006), http://fei.edu.br/~cet/ facedatabase.html
9. Luo, J., Ma, Y., Takikawa, E., Lao, S., Kawade, M., Lu, B.L.: Person-Specific SIFT Features for Face Recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2007, vol. 2, pp. II-593-II-596 (2007)
10. Lustig, M., Donoho, D.L., Pauly, J.M.: Rapid MR imaging with "compressed sensing" and randomly Under-Sampled 3DFT trajectories. In: ISMRM (2006)
11. Nowak, E., Jurie, F., Triggs, B.: Sampling strategies for bag-of-features image classification. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 490-503. Springer, Heidelberg (2006) (Pubitemid 44029653)
12. Rodriguez-Lujan, I., Huerta, R., Elkan, C., Cruz, C.S.: Quadratic programming feature selection. Journal of Machine Learning Research 11, 1491-1516 (2010)
13. Stein, S., Fink, G.: A new method for combined face detection and identification using interest point descriptors. In: IEEE International Conference on Automatic Face Gesture Recognition and Workshops (FG 2011), pp. 519-524 (2011)
14. Takhar, D., Laska, J., Wakin, M.B., Duarte, M.F., Baron, D., Sarvotham, S., Kelly, K., Baraniuk, R.: A new compressive imaging camera architecture using Optical-Domain compression. In: Proc. IS&T/SPIE Symposium on Electronic Imaging (2006)
15. Vapnik, V.: Statistical learning theory. Wiley (1998)