The Aware Home: A Living Laboratory for Ubiquitous Computing Research
CoBuild '99 Proceedings of the Second International Workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture
Text categorization by boosting automatically extracted concepts
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Boosting support vector machines for text classification through parameter-free threshold relaxation
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Common sense based joint training of human activity recognizers
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Detection of user mode shift in home
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Situation-Theoretic Analysis of Human Intentions in a Smart Home Environment
ICOST '09 Proceedings of the 7th International Conference on Smart Homes and Health Telematics: Ambient Assistive Health and Wellness Management in the Heart of the City
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To provide services according to user behavior, parameters should be adapted appropriately for the precise recognition of user behavior. In particular, the threshold value which is used to create behavioral patterns matched for behavior recognition impacts accuracy of behavior recognition. Because the threshold value is common to all users in the conventional model, the threshold setting unsuitable for some users may cause low recognition rates. In this paper, we propose a behavior detection method which detects high-level user behaviors, such as "leaving home". The proposed method achieves stable behavior recognition regardless of users, by introducing a model which dynamically determines the threshold value for individual user.