This article explores how placement variations in user-carried electronic appliances influence human action recognition and how such influence can be mitigated. The authors categorize possible variations into three classes: placement on different body parts (such as a jacket pocket versus a hip holster versus a trouser pocket), small displacement within a given coarse location (such as a device shifting in a pocket), and different orientations. For each of these variations, they present a systematic evaluation of the impact on human action recognition and give an overview of possible approaches to deal with them. They conclude with a detailed practical example on how to compensate for on-body placements variations that builds on an extension of their previous work. This article is part of a special issue on wearable computing.
- activity recognition
- inertial motion sensors
- pervasive computing
- placement variations
ASJC Scopus subject areas
- Computer Science Applications
- Computational Theory and Mathematics