Indoor localisation based on ubiquitous WLAN has exhibited the capability of being a cheap and relatively precise technology and has been verified by many successful examples. Its performance is subject to change due to multipath propagation and changes in the environment (people, building layouts, antenna characteristics etc.) which cannot be easily eliminated. This thesis addresses the automatic localisation of indoor user and proposes solutions for both positioning and seamlessly tracking a user using WLAN technology in addition to image sensing. By fusing these modalities we obtain better performance than using them individually. A fusion function designed to merge both analysis results into one semantic interpretation of user location is presented. Also a tracking approach based on an adaptive function that converts times between locations into probabilities and employs a Viterbi-based solution is proposed. An indoor localisation algorithm is described which is based on the creation of a database of WLAN signal strengths at pre-chosen calibration points (CPs). The need for fewer CPs than in standard methods is achieved due to the use of a novel interpolation algorithm, based on the specification of robust range and angle-dependent likelihood functions that describe the probability of a user being in the vicinity of each CP. The actual location of the user is estimated by solving a system of equations with two unknowns derived for a pair of CPs. Different pairs of CPs can be chosen to make several estimates which can then be combined to increase the accuracy of the estimate. The effectiveness of the fusion and the tracking approaches is evaluated on a very challenging dataset throughout a university building. Results that are presented demonstrate high accuracy that can be achieved. The methods are compared to several competing localisation methods and are shown to give superior results. The potential usefulness of this work is envisaged in a range of ambient assisted living applications including lifelogging and as an assistive technology for the memory or the visually impaired.