An Event-Driven Wearable System for Supporting Motorbike Racing Teams
ISWC '04 Proceedings of the Eighth International Symposium on Wearable Computers
An Event-driven Navigation Platform forWearable Computing Environments
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Model-Based Face De-Identification
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Landmark-Based Pedestrian Navigation with Enhanced Spatial Reasoning
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
SwimMaster: a wearable assistant for swimmer
Proceedings of the 11th international conference on Ubiquitous computing
IT-enabled donation boxes to promote donation
Proceedings of the International Conference on Advances in Computer Enterntainment Technology
Motionbeam: a metaphor for character interaction with handheld projectors
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
South by South-East or Sitting at the Desk: Can Orientation be a Place?
ISWC '11 Proceedings of the 2011 15th Annual International Symposium on Wearable Computers
Long term carefully learning for person detection application to intelligent surveillance system
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
Object-based activity recognition with heterogeneous sensors on wrist
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
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In recent years, technical improvements to sensors have attracted a great deal of attention, in particular due to the sensors' capability recognizing user contexts. In this paper, we propose an implicit context awareness system that identifies user context by sensing the context of surrounding environments. We implemented a prototype that recognizes user contexts by sensing surrounding people by two cameras We actually used the prototype in a variety of situations. Evaluation results showed that the system was effective and improved context recognition. Our method can be used to identify rich contexts that cannot be recognized by conventional methods.