I am reading the paper Selective Search for Object Recognition here. In Section 3.2, they give a similarity measure between two regions of an image based on the texture of the regions with what they refer to as "fast SIFT-like measurements". On page 4, bottom right side of the page, they write:
We take Gaussian derivatives in eight orientations using
$\sigma = 1$ for each colour channel. For each orientation for each colour channel we extract a histogram using a bin size of $10$.
I understand that a derivative of Gaussian filter is the filter of size $n \times n$ consisting of a discrete approximation of the derivative of a bivariate gaussian function of mean $0$ with some standard deviation.
What do the authors mean by "with eight orientations"? Is this some kind of modification to the filter? Any insights appreciated.