Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Ubiquitous Computing environment for aircraft maintenance
Proceedings of the 2004 ACM symposium on Applied computing
Convex Optimization
Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the scalability of semi-Markov conditional random fields for named entity recognition
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
Mobile Networks and Applications
Conditional random fields for activity recognition
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Activity Recognition for the Smart Hospital
IEEE Intelligent Systems
Discovery of activity patterns using topic models
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Detecting small group activities from multimodal observations
Applied Intelligence
Daily Routine Recognition through Activity Spotting
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Training conditional random fields using virtual evidence boosting
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Discriminative temporal smoothing for activity recognition from wearable sensors
UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems
Scalable recognition of daily activities with wearable sensors
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
Activity-oriented access control to ubiquitous hospital information and services
Information Sciences: an International Journal
EEM: evolutionary ensembles model for activity recognition in Smart Homes
Applied Intelligence
Mobile context inference using two-layered Bayesian networks for smartphones
Expert Systems with Applications: An International Journal
Multi levels semantic architecture for multimodal interaction
Applied Intelligence
Image annotation by modeling Supporting Region Graph
Applied Intelligence
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Activity recognition is becoming an important research area, and finding its way to many application domains ranging from daily life services to industrial zones. Sensing hardware and learning algorithms are two important components in activity recognition. For sensing devices, we prefer to use accelerometers due to low cost and low power requirement. For learning algorithms, we propose a novel implementation of the semi-Markov Conditional Random Fields (semi-CRF) introduced by Sarawagi and Cohen. Our implementation not only outperforms the original method in terms of computation complexity (at least 10 times faster in our experiments) but also is able to capture the interdependency among labels, which was not possible in the previously proposed model. Our results indicate that the proposed approach works well even for complicated activities like eating and driving a car. The average precision and recall are 88.47% and 86.68%, respectively, which are higher than results obtained by using other methods such as Hidden Markov Model (HMM) or Topic Model (TM).