Document Type
Conference Proceeding
Publication Date
12-2012
Department
Computer Engineering and Computer Science
Abstract
Captchas are frequently used on the modern world wide web to differentiate human users from automated bots by giving tests that are easy for humans to answer but difficult or impossible for algorithms. As artificial intelligence algorithms have improved, new types of Captchas have had to be developed. Recent work has proposed a new system called Avatar Captcha, in which a user is asked to distinguish between facial images of real humans and those of avatars generated by computer graphics. This novel system has been proposed on the assumption that this Captcha is very difficult for computers to break. In this paper we test a variety of modern visual features and learning algorithms on this avatar recognition task. We find that relatively simple techniques can perform very well on this task, and in some cases can even surpass human performance. © 2012 IEEE.
Original Publication Information
M. Korayem, A. A. Mohamed, D. Crandall and R. V. Yampolskiy, "Learning Visual Features for the Avatar Captcha Recognition Challenge," 2012 11th International Conference on Machine Learning and Applications, 2012, pp. 584-587, doi: 10.1109/ICMLA.2012.200.
ThinkIR Citation
Korayem, Mohammed; Mohamed, Abdallah A.; Crandall, David; and Yampolskiy, Roman, "Learning visual features for the avatar Captcha recognition challenge" (2012). Faculty Scholarship. 633.
https://ir.library.louisville.edu/faculty/633
DOI
10.1109/ICMLA.2012.200
ORCID
0000-0001-9637-1161
