Watman, CraigAustin, DavidBarnes, NicholasOverett, GaryThompson, Simon2015-12-132015-12-13April 26 20780382323http://hdl.handle.net/1885/78120This paper presents various optimisations that can be applied to the Sum of Absolute Differences (SAD) correlation algorithm for automated landmark detection. This has applications in mobile robotic navigation and mapping. We show how some assumptions about the environment and the generic form of strong landmarks selected by the SAD correlation algorithm have led to the development of an algorithm to enable near real time selection of strong landmarks from visual information. The landmarks that have been selected from a series of frames using our optimisations are shown to be stable through the image sequence, demonstration the scale invariance of the landmarks that are selected by the SAD correlation algorithm.Keywords: Algorithms; Correlation methods; Information retrieval; Mapping; Navigation; Optimization; Problem solving; Tracking (position); Mobile robotic navigation; Normalized cross correlation (NCC); Sum of absolute differences (SAD); Visual landmark detector; MoFast Sum of Absolute Differences Visual Landmark Detector20042015-12-11