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26 February 2008Rapid object candidate detection using increment sign correlation
We develop a rapid object-candidates detector using Increment Sign Correlation (ISC). Our method aims to detect
candidates of objects such as people or vehicles in real time using ISC and a simple shape model. Our method is similar
to Generalized Hough Transform (GHT). However we modify its voting process. We use ISC for detecting object
candidates instead of the shape voting done by GHT. ISC is robust against shading and low image contrast due to
lighting changes because Increment Sign (IS) is insensitive to a perturbation of direction of intensity gradient. The
computational cost of IS is lower than that of the gradient also. From the results of our experiment, our detector can run
with a 320×240 pixel image within 32 milliseconds on a Pentium 4 processor at 2.8 GHz. Given the initial template size
of 10×20 pixels, the number of candidates decreases from 170,196 sub-windows in a 320×240 pixel image to 400 at
most with the miss rate of 0.2 %. The detection rate is enough for more precise detectors which need to use richer image
features. The experimental results using real image sequences are reported.