19 May 2011 Dismounted human detection at long ranges
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Abstract
This research investigates the automatic detection of a dismounted human from a single image as a function of range. The histogram of oriented gradients (HOG) method provides the feature vector and a support vector machine performs the classification. This work presents, for the first time, an understanding of how HOG for human detection holds up as range increases. The results indicate that HOG remains effective even at long distances; for example, the average miss rate and false alarm rate were both kept to 5% for humans only 12 pixels high and 4-5 pixels wide. The impact of the amount and type of training data needed to achieve this long-range performance is examined.
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Amy E. Bell, Amy E. Bell, } "Dismounted human detection at long ranges", Proc. SPIE 8049, Automatic Target Recognition XXI, 80490J (19 May 2011); doi: 10.1117/12.883489; https://doi.org/10.1117/12.883489
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