Incremental salient point detection

In this paper, we investigate an approach that computes salient points, i.e. areas of natural images that contain corners or edges, incrementally. We focus on the popular Harris corner detector and demonstrate how such an approach can operate when the image samples are refined in a bitwise manner, i.e. the image bitplanes are received one-by-one from the image sensor. This has the advantage that the image sensing and the salient point detection can be terminated at any input image precision (e.g. at a bound set by the sensory equipment or by computation, or by the salient point accuracy required by the application) and the obtained salient points under this precision are readily available. We estimate the required energy for image sensing as well as the computation required for the salient point detection and compare them against the conventional salient point detector realization that operates directly on each source precision and cannot refine the result. Our experiments demonstrate the feasibility of incremental approaches for salient point detection in various classes of natural images. In addition, a first comparison between the results obtained by the intermediate detectors is presented.