SLAM – Loop Closing with Visually Salient Features Paul Newman, Kin Leong Ho Oxford University Robotics Research Group

Motivation Loop Closing – the task of deciding whether a vehicle has returned to a previously visited area Popular approaches – nearest neighbour statistical gate, joint compatibility test Closing loop with visually salient features to avoid dependence on global position estimate

Visual Saliency Scale saliency detector [ Kadir/Brady IJCV 2001] - form p.d.f. of pixel properties within local region at varying scales for each pixel detection of region at a particular scale where weighted entropy is peaked selected regions are considered more “interesting” p.d.f of local pixels over scale s around position x entropy

Visual Saliency Dissimilarity p.d.f of across scale Weighting Function Saliency metric entropy Weighting function

Wide-Baseline Stability Maximally stable extremal region (MSER) detector [ Matas etal. BMVC 2002] -pixels taking on values in the range D = {dmin ….dmax}

MSER detector Saliency detector

Feature Description -Scale invariant feature transform (SIFT) descriptor [David Lowe IJCV 2004] -128 dimensional descriptor

MSER Detector Query Image Selected Regions SIFT Descriptor Saliency Detector Similarity Measure Matched Images Laser Scan Database Image Database

Demonstration of wide-baseline stability of visually salient features under perspective distortion and variation in illumination conditions

Matching Performance Similar posters found in the environment.

A Delayed State Formulation Control Past poses Scan matching between Past poses produces observation z with which to update state-vector State vector contains only past vehicle poses. (Atlas IJRR 2004 )

Delayed State Formulation II EKF update

Closing Small Loops

Closing Big Loops

Closing the loop

Issues -hard decision making -using saliency detector as binary selector -repetitive visual features in urban environment

Demonstration

Questions Thank you!