Corners are important features in images because they typically delimit the boundaries of regions or objects. For real-time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner detectors and able to be computed and matched at video rate: one encodes the entire region within a corner, whereas the other describes only the region within an object. The advantage of encoding only the region within an object is demonstrated. The noise stability of the descriptors is assessed and compared with that of the popular binary robust independent elementary feature (BRIEF) descriptor, and the matching performances of the descriptors are compared on video sequences from hand-held cameras and the PETS2012 database. A statistical analysis shows that performance is indistinguishable from BRIEF.

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Matching corners using the informative arc

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