Telling computers and humans apart automatically using activity recognition

This paper proposes a new image based CAPTCHA test, Activity Recognition CAPTCHA. In this test the user is presented with a set of distorted images depicting a randomly chosen activity. The user has to recognize the common activity associated with the images and annotate it from a given list of activities to pass the test. The user studies indicate that this CAPTCHA can be solved with 99.04% average pass rate while that of ESP PIX CAPTCHA is 85.44% and SQUIGL PIX is 67.84%. Average time taken to pass the test is less than 10 seconds.

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