Context and consciousness: activity theory and human-computer interaction
Context and consciousness: activity theory and human-computer interaction
Machine Learning
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Sensing from the basement: a feasibility study of unobtrusive and low-cost home activity recognition
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
Accurate activity recognition in a home setting
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Improving the recognition of interleaved activities
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Sensor Information Management Mechanism for Context-aware Service in Ubiquitous Home
IEEE Transactions on Consumer Electronics
A life log collector integrated with a remote-controller for enabling user centric services
IEEE Transactions on Consumer Electronics
Automatic video-based human motion analyzer for consumer surveillance system
IEEE Transactions on Consumer Electronics
UMONS: Ubiquitous monitoring system in smart space
IEEE Transactions on Consumer Electronics
Ontology-based semantic recommendation system in home network environment
IEEE Transactions on Consumer Electronics
Mobile context inference using two-layered Bayesian networks for smartphones
Expert Systems with Applications: An International Journal
Science of Computer Programming
Building health persona from personal data streams
Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia
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Activity recognition is a core aspect of ubiquitous computing applications. In order to deploy activity recognition systems in the real world, we need simple sensing systems with lightweight computational modules to accurately analyze sensed data. In this paper, we propose a simple method to recognize human activities using simple object information involved in activities. We apply activity theory for representing complex human activities and propose a penalized naive Bayes classifier for performing activity recognition. Our results show that our method reduces computation up to an order of magnitude in both learning and inference without penalizing accuracy, when compared to hidden Markov models and conditional random fields.