Location is a key information for context-aware systems. While coarse-grained
indoor location estimates may be obtained quite easily (e.g. based on WiFi or
GSM), finer-grained estimates typically require additional infrastructure (e.g.
ultrasound). This work explores an approach to estimate significant places,
e.g., at the fridge, with no additional setup or infrastructure. We use a
pocket-based inertial measurement sensor, which can be found in many recent
phones. We analyze how the spatial layout such as geographic orientation of
buildings, arrangement and type of furniture can serve as the basis to estimate
typical places in a daily scenario. Initial experiments reveal that our
approach can detect fine-grained locations without relying on any
infrastructure or additional devices.