Abstract
In this paper, we propose a dense motion segmentation method for human daily activity recognition from a wearable device - 'Smart Glasses'. The glasses are embedded with a camera, which allows the system to automatically recognise the wearer's activities from a first-person perspective. This application can be broadly applied to patients, elderly, safety workers, e-health monitoring, or anyone requiring cognitive assistance or guidance on their activities of daily living (ADLs). We validate our system in challenging real-world scenarios, and compare two feature extraction approaches: averaged optical flow and a combined dense motion segmentation approach. We classify them using LogitBoost (on Decision Stumps) and Support Vector Machine (SVM). We also suggest the optimal settings of the classifiers through cross-validation over our ADLs database. The results show that the optical flow with average pooling has a good performance when classifying general locomotive activities. The results also indicate the benefits that dense motion segmentation features can have on reliably classify activities involving a moving object, such as hands. We achieve an overall accuracy of up to 69.76% on 12 ADLs using local classifiers, and with a Hidden Markov Model (HMM) process this accuracy improves to up to 89.59%.
Original language | English |
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Title of host publication | 13th International Conference on Control, Automation, Robotics and Vision, ICARCV 2014 |
Subtitle of host publication | Marina Bay Sands, Singapore, 10-12th December 2014 |
Editors | Han Wang |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 123 - 128 |
Number of pages | 6 |
ISBN (Electronic) | 9781479951994 |
ISBN (Print) | 9781479952007 |
DOIs | |
Publication status | Published - 2014 |
Externally published | Yes |
Event | International Conference on Control, Automation, Robotics and Vision 2014 - Marina Bay Sands, Singapore Duration: 10 Dec 2014 → 12 Dec 2014 Conference number: 13th https://ieeexplore.ieee.org/xpl/conhome/7056237/proceeding (Proceedings) |
Conference
Conference | International Conference on Control, Automation, Robotics and Vision 2014 |
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Abbreviated title | ICARCV 2014 |
Country/Territory | Singapore |
City | Marina Bay Sands |
Period | 10/12/14 → 12/12/14 |
Internet address |