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Emerging applications, such as indoor navigation or facility management, present new requirements of automatic and robust partitioning of indoor 3D point clouds into rooms. Previous research is either based on the Manhattan-world assumption or relies on the availability of the scanner pose information. We address these limitations by following the architectural definition of a room, where the room...
We propose an inertial sensor-based approach to activity recognition for pedestrian indoor navigation. In the considered scenario a mobile device is held in a hand in front of the user. The recognized activities are the ones relevant to positioning in multi-floor buildings: walking and going up or down the stairs. To model the time dependency between consecutive activities we employ a Hidden Markov...
Pedestrian navigation is an important ingredient for efficient multimodal transportation, such as guidance within large transportation infrastructures. A requirement is accurate positioning of people in indoor multistory environments. To achieve this, maps of the environment play a very important role. FootSLAM is an algorithm based on the simultaneous localization and mapping (SLAM) principle that...
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