Layered Representations for Human Activity Recognition
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Modeling Individual and Group Actions in Meetings: A Two-Layer HMM Framework
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 7 - Volume 07
Unsupervised clustering of ambulatory audio and video
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Discovery of activity patterns using topic models
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
A new approach to enable gesture recognition in continuous data streams
ISWC '08 Proceedings of the 2008 12th IEEE International Symposium on Wearable Computers
Using rhythm awareness in long-term activity recognition
ISWC '08 Proceedings of the 2008 12th IEEE International Symposium on Wearable Computers
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Scalable recognition of daily activities with wearable sensors
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
Passive and In-Situ assessment of mental and physical well-being using mobile sensors
Proceedings of the 13th international conference on Ubiquitous computing
Semi-Markov conditional random fields for accelerometer-based activity recognition
Applied Intelligence
Review: Situation identification techniques in pervasive computing: A review
Pervasive and Mobile Computing
Ambient Assisted Living system for in-home monitoring of healthy independent elders
Expert Systems with Applications: An International Journal
Mining user similarity based on routine activities
Information Sciences: an International Journal
A tutorial on human activity recognition using body-worn inertial sensors
ACM Computing Surveys (CSUR)
Towards Collaborative Group Activity Recognition Using Mobile Devices
Mobile Networks and Applications
Towards scalable activity recognition: adapting zero-effort crowdsourced acoustic models
Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia
Human activity recognition using social media data
Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia
| Hi-index | 0.00 |
This paper explores the possibility of using low-level activity spotting for daily routine recognition. Using occurrence statistics of low-level activities and simple classifiers based on their statistics allows to train a discriminative classifier for daily routine activities such as working and commuting. Using a recently published data set we find that the number of required low-level activities is surprisingly low, thus, enabling efficient algorithms for daily routine recognition through low-level activity spotting. More specifically we employ the JointBoosting-framework using low-level activity spotters as weak classiers. By using certain low-level activities as support, we achieve an overall recall rate of over 90% and precision rate of over 88%. Tuning down the weak classifiers using only 2.61% of the original data still yields recall and precision rates of 80% and 83%.