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A novel local intensity distribution (LID) descriptor for object detection is proposed. By capturing the distribution of local intensity differences effectively, the LID descriptor is insensitive to illumination changes while being more compact and discriminative compared with the popular local binary pattern. Two LID descriptors can be efficiently compared using the Kullback-Leibler distance. The efficacy and efficiency of the proposed descriptor have been verified in the task of detecting humans from static images.