Using location, bearing and motion data to filter video and system logs

Abstract

In evaluating and analysing a pervasive computing system, it is common to log system use and to create video recordings of users. A lot of data will often be generated, representing potentially long periods of user activity. We present a procedure to identify sections of such data that are salient given the current context of analysis; for example analysing the activity of a particular person among many trial participants recorded by multiple cameras. By augmenting the cameras used to capture a mobile experiment, we are able to establish both a location and heading for each camera, and thus model the field of view for each camera over time. Locations of trial participants are also recorded and compared against camera views, to determine which periods of user activity are likely to have been recorded in detail. Additionally the stability of a camera can be tracked and video can be subsequently filtered to exclude footage of unacceptable quality. These techniques are implemented in an extension to Replayer, a software toolkit for use in the development cycle of mobile applications. A report of initial testing is given, whereby the technique's use is demonstrated on a representative mobile application. © Springer-Verlag Berlin Heidelberg 2007.