Adaptive pedestrian activity classification for indoor dead reckoning systems

Sara Khalifa, Mahbub Hassan, Aruna Seneviratne
2013 International Conference on Indoor Positioning and Indoor Navigation  
A pedestrian activity classification (PAC) system classifies pedestrian motion data into activities related to the usage of specific building facilities, such as going up on an escalator or descending a staircase. Recent studies confirm that use of PAC significantly reduces indoor localization errors of a pedestrian dead reckoning (PDR) system as exact facility locations in the building can be retrieved from the floor map. However, classification complexity may become an issue for resource
more » ... raint mobile devices. We propose a novel PAC system that, instead of using a single complex classifier based on a large set of features, employs multiple simple classifiers each trained to classify only a subset of the activities using a small number of features. As the pedestrian moves around inside a building, the proposed adaptive-PAC dynamically switches to the right (simple) classifier based on the facilities that exist within the immediate proximity. By always using a simple classifier, adaptive-PAC has the potential to drastically reduce the average classification complexity for PAC-aided PDR systems. Using experimental data, we quantify and compare the performance of the proposed adaptive-PAC against the conventional PAC. We find that for typical shopping centers, adaptive-PAC reduces classification complexity by 91-97% without any degradation in classification accuracy rates.
doi:10.1109/ipin.2013.6817868 dblp:conf/ipin/KhalifaHS13 fatcat:xqxvvnzb2jfjfp4zlzmizt2lum