Image-guided Tours: Fast-approximated Sift with U-surf Features
نویسندگان
چکیده
In this paper, a feature-detecting algorithm to identify paintings from mobile phone camera images is presented. The algorithm is capable of identifying paintings from noisy camera-phone images. Even with typical blurring, rotation, and a small amount of perspective distortion that would occur in a controlled museum setting, by training on a set of standard painting images, the paintings can be correctly identified. With calculation-intensive portions of the code in C, the algorithm runs efficiently as well as accurately. All 99 test images were detected correctly, with an average runtime of 0.9228 seconds on SCIEN machines.
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