Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Human motion analysis: a review
Computer Vision and Image Understanding
Increasing the opportunities for aging in place
CUU '00 Proceedings on the 2000 conference on Universal Usability
An open agent architecture for assisting elder independence
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Human Activity Recognition Using Multidimensional Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Parameterized Modeling and Recognition of Activities
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Survey of Text Mining
Pervasive Computing Research on Aging, Disability and Independence
SAINT-W '04 Proceedings of the 2004 Symposium on Applications and the Internet-Workshops (SAINT 2004 Workshops)
Mining models of human activities from the web
Proceedings of the 13th international conference on World Wide Web
Technology for Care Networks of Elders
IEEE Pervasive Computing
Dining Activity Analysis Using a Hidden Markov Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Inferring Activities from Interactions with Objects
IEEE Pervasive Computing
A data mining approach for location prediction in mobile environments
Data & Knowledge Engineering
Conditional Random Fields for Contextual Human Motion Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Text document clustering based on frequent word sequences
Proceedings of the 14th ACM international conference on Information and knowledge management
Fine-Grained Activity Recognition by Aggregating Abstract Object Usage
ISWC '05 Proceedings of the Ninth IEEE International Symposium on Wearable Computers
Activity Recognition of Assembly Tasks Using Body-Worn Microphones and Accelerometers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised analysis of activity sequences using event-motifs
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
The Journal of Machine Learning Research
Activity Recognition using Dynamic Bayesian Networks with Automatic State Selection
WMVC '07 Proceedings of the IEEE Workshop on Motion and Video Computing
Unsupervised activity recognition using automatically mined common sense
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Activity recognition from accelerometer data
IAAI'05 Proceedings of the 17th conference on Innovative applications of artificial intelligence - Volume 3
Inferring long-term user properties based on users' location history
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A long-term evaluation of sensing modalities for activity recognition
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Portable wireless sensors for object usage sensing in the home: challenges and practicalities
AmI'07 Proceedings of the 2007 European conference on Ambient intelligence
Unsupervised discovery of structure in activity data using multiple eigenspaces
LoCA'06 Proceedings of the Second international conference on Location- and Context-Awareness
Activity recognition using temporal evidence theory
Journal of Ambient Intelligence and Smart Environments
A top-level ontology for smart environments
Pervasive and Mobile Computing
Building a real-world body area sensor network system
Proceedings of the Second Asia-Pacific Symposium on Internetware
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
A hierarchical approach to real-time activity recognition in body sensor networks
Pervasive and Mobile Computing
The application of machine-learning on lower limb motion analysis in human exoskeleton system
ICSR'12 Proceedings of the 4th international conference on Social Robotics
Managing context data for diverse operating spaces
Pervasive and Mobile Computing
Segmenting sensor data for activity monitoring in smart environments
Personal and Ubiquitous Computing
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Activity recognition on streaming sensor data
Pervasive and Mobile Computing
Learning a taxonomy of predefined and discovered activity patterns
Journal of Ambient Intelligence and Smart Environments
Hi-index | 0.00 |
Monitoring daily activities of a person has many potential benefits in pervasive computing. These include providing proactive support for the elderly and monitoring anomalous behaviors. A typical approach in existing research on activity detection is to construct sequence-based models of low-level activity features based on the order of object usage. However, these models have poor accuracy, require many parameters to estimate, and demand excessive computational effort. Many other supervised learning approaches have been proposed but they all suffer from poor scalability due to the manual labeling involved in the training process. In this paper, we simplify the activity modeling process by relying on the relevance weights of objects as the basis of activity discrimination rather than on sequence information. For each activity, we mine the web to extract the most relevant objects according to their normalized usage frequency. We develop a KeyExtract algorithm for activity recognition and two algorithms, MaxGap and MaxGain, for activity segmentation with linear time complexities. Simulation results indicate that our proposed algorithms achieve high accuracy in the presence of different noise levels indicating their good potential in real-world deployment.