Abstract. Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling contextaware applications. As most approache...
Abstract. We propose a novel model-based approach to activity recognition using high-level primitives that are derived from a human body model estimated from sensor data. Using sho...
This paper explores the possibility of using low-level activity spotting for daily routine recognition. Using occurrence statistics of lowlevel activities and simple classifiers b...
Outdoor location-based services are now prevalent due to advances in mobile technology and GPS. Indoors, however, even coarse location remains unavailable. Bluetooth has been ident...
Abstract. Wireless signal strength fingerprinting has become an increasingly popular technique for realizing indoor localization systems using existing WiFi infrastructures. Howev...
Philipp Bolliger, Kurt Partridge, Maurice Chu, Mar...
This paper presents two algorithms, non-linear regression and Kalman filtering, that fuse heterogeneous data (pseudorange and angle-of-arrival) from an ultra-wideband positioning ...
With proliferation of ubiquitous computing, digital access is facing an increasing risk since unauthorized client located at any place may intrude a local server. Location Based Ac...
Abstract. Location-based Services are emerging as popular applications in pervasive computing. Spatial k-anonymity is used in Locationbased Services to protect privacy, by hiding t...
802.11-based indoor positioning systems have been under research for quite some time now. However, despite the large attention this topic has gained, most of the research focused o...