X-Faces: The eXploit Is Out There

Aus de_evolutionary_art_org
Version vom 31. Dezember 2016, 18:52 Uhr von Gubachelier (Diskussion | Beiträge) (Die Seite wurde neu angelegt: „ == Reference == Joao Correia, Tiago Martins, Pedro Martins and Penousal Machado: X-Faces: The eXploit Is Out There. In: Computational Creativity 2016 I…“)

(Unterschied) ← Nächstältere Version | Aktuelle Version (Unterschied) | Nächstjüngere Version → (Unterschied)
Wechseln zu: Navigation, Suche


Reference

Joao Correia, Tiago Martins, Pedro Martins and Penousal Machado: X-Faces: The eXploit Is Out There. In: Computational Creativity 2016 ICCC 2016, 164-171

DOI

Abstract

In the combinatorial form of creativity novel ideas are produced through unfamiliar combinations of familiar ideas. We explore this type of creativity in the scope of Data Augmentation applied to Face Detection. Typically, the creation of face detectors requires the construction of datasets of examples to train, test, and validate a classifier, which is a troublesome task. We propose a Data Augmentation technique to autonomously generate new frontal faces out of existing ones. The elementary parts of the faces are recombined using Evolutionary Computation and Computer Vision techniques. The key novel contributions include: (i) an approach capable of automatically creating face alternatives; (ii) the creation and usage of computational curators to automatically select individuals from the evolutionary process; and (iii) an experimentation with the interplay between Data Augmentation and serendipity. The system tends to create a wide variety of unexpected faces that exploit the vulnerabilities of face detectors. The overall results suggest that our approach is a viable Data Augmentation approach in the field of Face Detection.

Extended Abstract

Bibtex

@inproceedings{
 author = {Joao Correia, Tiago Martins, Pedro Martins and Penousal Machado},
 title = {X-Faces: The eXploit Is Out There},
 booktitle = {Proceedings of the Seventh International Conference on Computational Creativity},
 series = {ICCC2016},
 year = {2016},
 month = {Jun-July},
 location = {Paris, France},
 pages = {164-171},
 url = {http://www.computationalcreativity.net/iccc2016/wp-content/uploads/2016/01/X-Faces-The-eXploit-Is-Out-There.pdf http://de.evo-art.org/index.php?title=X-Faces:_The_eXploit_Is_Out_There },
 publisher = {Sony CSL Paris},
}


Used References

[2009] Boden, M. A. 2009. Computer models of creativity. AI Magazine 30(3):23.

[2007] Chen, J.; Wang, R.; Yan, S.; Shan, S.; Chen, X.; and Gao, W. 2007. Enhancing human face detection by resampling examples through manifolds. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on 37(6):1017–1028.

[2004] Chen, J.; Chen, X.; and Gao, W. 2004. Resampling for face detection by self-adaptive genetic algorithm. In Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on, volume 3, 822 – 825 Vol.3.

[2013] Correia, J.; Machado, P.; Romero, J.; and Carballal, A. 2013. Evolving figurative images using expression-based evolutionary art. In Proceedings of the fourth International Conference on Computational Creativity (ICCC), 24–31.

[2009] DiPaola, S. R., and Gabora, L. 2009. Incorporating characteristics of human creativity into an evolutionary art algorithm. Genetic Programming and Evolvable Machines 10(2):97–110.

[1995] Freund, Y., and Schapire, R. E. 1995. A decisiontheoretic generalization of on-line learning and an application to boosting. In Proceedings of the Second European Conference on Computational Learning Theory, EuroCOLT ’95, 23–37. London, UK, UK: Springer-Verlag.

[2004] Frowd, C. D.; Hancock, P. J. B.; and Carson, D. 2004. EvoFIT: A holistic, evolutionary facial imaging technique for creating composites. ACM Transactions on Applied Perception 1(1):19–39.

[1997] Johnston, V. S., and Caldwell, C. 1997. Tracking a criminal suspect through face space with a genetic algorithm. In B¨ack, T.; Fogel, D. B.; and Michalewicz, Z., eds., Handbook of Evolutionary Computation. Bristol, New York: Institute of Physics Publishing and Oxford University Press. G8.3:1–8.

[2007] Liao, S.; Zhu, X.; Lei, Z.; Zhang, L.; and Li, S. Z. 2007. Learning multi-scale block local binary patterns for face recognition. In Proceedings of the 2007 International Conference on Advances in Biometrics, ICB’07, 828–837. Berlin, Heidelberg: Springer-Verlag.

[2002] Lienhart, R.; Kuranov, A.; and Pisarevsky, V. 2002. Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection. Computing 2781(MRL):297–304.

[2009] MacDorman, K. F.; Green, R. D.; Ho, C.-C.; and Koch, C. T. 2009. Too real for comfort? uncanny responses to computer generated faces. Computers in Human Behavior 25(3):695 – 710. Including the Special Issue: Enabling elderly users to create and share self authored multimedia content.

[2015] Machado, P.; Vinhas, A.; Correia, J.; and Ek´art, A. 2015. Evolving ambiguous images. In Yang, Q., and Wooldridge, M., eds., Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, July 25-31, 2015, 2473– 2479. AAAI Press.

[2012a] Machado, P.; Correia, J.; and Romero, J. 2012a. Expression-based evolution of faces. In Evolutionary and Biologically Inspired Music, Sound, Art and Design - First International Conference, EvoMUSART 2012, M´alaga, Spain, April 11-13, 2012. Proceedings, volume 7247 of Lecture Notes in Computer Science, 187–198. Springer.

[2012b] Machado, P.; Correia, J.; and Romero, J. 2012b. Improving face detection. In Moraglio, A.; Silva, S.; Krawiec, K.; Machado, P.; and Cotta, C., eds., Genetic Programming - 15th European Conference, EuroGP 2012, M´alaga, Spain, April 11-13, 2012. Proceedings, volume 7244 of Lecture Notes in Computer Science, 73–84. Springer.

[1996] Ojala, T.; Pietik¨ainen, M.; and Harwood, D. 1996. A comparative study of texture measures with classification based on feature distributions. Pattern Recognition 29(1):51–59.

[2013] Pease, A.; Colton, S.; Ramezani, R.; Charnley, J.; and Reed, K. 2013. A discussion on serendipity in creative systems. In Proceedings of the Fourth International Conference on Computational Creativity, 64.

[2003] P´erez, P.; Gangnet, M.; and Blake, A. 2003. Poisson image editing. In ACM Transactions on Graphics (TOG), volume 22, 313–318. ACM.

[2014] Schorlemmer, M.; Smaill, A.; K¨uhnberger, K.-U.; Kutz, O.; Colton, S.; Cambouropoulos, E.; and Pease, A. 2014. Coinvent: Towards a computational concept invention theory. In Proceedings of the Fifth International Conference on Computational Creativity, ICCC2014, 288–296. International Association for Computational Creativity.

[1998] Sung, K.-K., and Poggio, T. 1998. Example-based learning for view-based human face detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on 20(1):39–51.

[2010] Ventrella, J. 2010. Self portraits with mandelbrot genetics. In Proceedings of the 10th international conference on Smart graphics, SG’10, 273–276. Berlin, Heidelberg: Springer-Verlag.

[2001] Viola, P., and Jones, M. 2001. Rapid object detection using a boosted cascade of simple features. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, I–511–I–518 vol.1.

[2002] Yang, M.-H.; Kriegman, D.; and Ahuja, N. 2002. Detecting faces in images: a survey. Pattern Analysis and Machine Intelligence, IEEE Transactions on 24(1):34–58.

[2010] Zhang, C., and Zhang, Z. 2010. A survey of recent advances in face detection. Technical report, Tech. rep., Microsoft Research.


Links

Full Text

http://www.computationalcreativity.net/iccc2016/wp-content/uploads/2016/01/X-Faces-The-eXploit-Is-Out-There.pdf

intern file

Sonstige Links