Privacy risk models for designing privacy-sensitive ubiquitous computing systems
DIS '04 Proceedings of the 5th conference on Designing interactive systems: processes, practices, methods, and techniques
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Sustained logging and discrimination of sleep postures with low-level, wrist-worn sensors
ISWC '08 Proceedings of the 2008 12th IEEE International Symposium on Wearable Computers
UBI-Hotspot 1.0: Large-Scale Long-Term Deployment of Interactive Public Displays in a City Center
ICIW '10 Proceedings of the 2010 Fifth International Conference on Internet and Web Applications and Services
Robust Pose Recognition of the Obscured Human Body
International Journal of Computer Vision
Combining wearable and environmental sensing into an unobtrusive tool for long-term sleep studies
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
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Designing and installing long-term monitoring equipment in the users' home sphere often presents challenges in terms of reliability, privacy, and deployment. Taking the logging of sleeping postures as an example, this study examines data from two very different modalities, high-fidelity video footage and logged wrist acceleration, that were chosen for their ease of setting up and deployability for a sustained period. An analysis shows the deployment challenges of both, as well as what can be achieved in terms of detection accuracy and privacy. Finally, we evaluate the benefits that a combination of both modalities would bring.