Efficient multi-viewpoint acquisition of 3D objects undergoing repetitive motions
Proceedings of the 2007 symposium on Interactive 3D graphics and games
Local velocity-adapted motion events for spatio-temporal recognition
Computer Vision and Image Understanding
Finding repetitive patterns in 3D human motion captured data
Proceedings of the 2nd international conference on Ubiquitous information management and communication
International Journal of Computer Vision
Video synchronization and its application to object transfer
Image and Vision Computing
IEEE Transactions on Image Processing
Temporal synchronization of non-overlapping videos using known object motion
Pattern Recognition Letters
Aligning spatio-temporal signals on a special manifold
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Comparative study of segmentation of periodic motion data for mobile gait analysis
WH '10 Wireless Health 2010
Kernelized temporal cut for online temporal segmentation and recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Spatio-temporal LTSA and its application to motion decomposition
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
View invariant action recognition using weighted fundamental ratios
Computer Vision and Image Understanding
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
Computational behaviour modelling for autism diagnosis
Proceedings of the 15th ACM on International conference on multimodal interaction
Temporal segmentation and assignment of successive actions in a long-term video
Pattern Recognition Letters
Detecting bipedal motion from correlated probabilistic trajectories
Pattern Recognition Letters
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A method for defecting and segmenting periodic motion is presented. We exploit periodicity as a cite and detect periodic motion in complex scenes where common methods for rnotion segmentation are likely to fail. We note that periodic motion detection can be seen as an approximate case of sequence alignment where an image sequence is matched to itself over one or more periods of time. To use this observation, we first consider alignment of two video sequences obtained by independently moving cameras. Under assumption of constant translation, the fundamental matrices and the homographies are shown to be time-linear matrix functions. These dynamic quantities can be estimated by matching corresponding space-time points with similar local motion and shape. For periodic motion, we match corresponding points across periods and develop a RANSAC procedure to simultaneously estimate the period and the dynamic geometric transformations between periodic views. Using this method, we demonstrate detection and segmentation of human periodic motion in complex scenes with non-rigid backgrounds, moving camera and motion parallax.