Learning to track the visual motion of contours
Artificial Intelligence - Special volume on computer vision
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Periodic Motion Detection and Estimation via Space-Time Sampling
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Body Tracking in HumanWalk from Monocular Video Sequences
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Periodic Motion Detection and Segmentation via Approximate Sequence Alignment
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Orient-2: a realtime wireless posture tracking system using local orientation estimation
Proceedings of the 4th workshop on Embedded networked sensors
Generic temporal segmentation of cyclic human motion
Pattern Recognition
Distributed Continuous Action Recognition Using a Hidden Markov Model in Body Sensor Networks
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
A Distributed Hidden Markov Model for Fine-grained Annotation in Body Sensor Networks
BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks
An automatic segmentation technique in body sensor networks based on signal energy
BodyNets '09 Proceedings of the Fourth International Conference on Body Area Networks
Recognition and segmentation of 3-d human action using HMM and multi-class adaboost
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Proceedings of the 12th international conference on Information processing in sensor networks
Latent space segmentation for mobile gait analysis
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on Wireless Health Systems, On-Chip and Off-Chip Network Architectures
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Two approaches are presented and compared for segmenting motion data from on-body Orient wireless motion capture system for mobile gait analysis. The first is a basic, model-based algorithm which operates directly on the joint angles computed by the Orient sensor devices. The second is a model-free, Latent Space algorithm, which first aggregates all the sensor data, and then embeds them in a low-dimensional manifold to perform segmentation. The two approaches are compared for segmenting four different styles of walking, and then applied in a hospital-based clinical study for analysing the motion of elderly patients recovering from a fall.