In general, binary descriptors have been used for tasks like texture analysis, recognition, and matching, e.g., LBP13,18 and the CT.12 In the context of local descriptors, several fast binary descriptors were also developed recently, e.g., BRIEF,10 BRISK,14 FREAK,15 etc. In our experiments, we considered the center-based descriptors CENSUS and LBP, where center-based refers to the fact that pairwise comparison always involves the central pixel, and the uncentered descriptors BRIEF and STABLE. The main difference in binary descriptors is in the sampling pattern for local intensity comparisons, which results in a binary descriptor vector. The CENSUS-dense descriptor is the only descriptor utilizing exactly all pixels in the considered matching window. We alternatively investigate the CENSUS-sparse descriptor, which uses a subsample of off-center pixels on a regular grid and compares those against the central pixel. The BRIEF descriptor uses a subsample of pixel pairs (typically sparsely) located at arbitrary positions in the matching window. The resulting descriptor lengths equal the number of pixel pair comparisons performed. Finally, with STABLE, we also get pixel pairs at random positions, but we are able to map a larger number of pixel pairs to a smaller number of descriptor bits. Figure 5 shows the compared descriptor masks (the meaning of the numbers in the mask will be explained in the next section).