Kernel independent component analysis
The Journal of Machine Learning Research
Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
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
Statistical Analysis of Dynamic Actions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling changing dependency structure in multivariate time series
Proceedings of the 24th international conference on Machine learning
A tutorial on spectral clustering
Statistics and Computing
A Hilbert Space Embedding for Distributions
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
International Journal of Computer Vision
Modeling the temporal extent of actions
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Modeling temporal structure of decomposable motion segments for activity classification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Detecting unusual activity in video
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Making action recognition robust to occlusions and viewpoint changes
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
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
Joint segmentation and classification of human actions in video
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
An online kernel change detection algorithm
IEEE Transactions on Signal Processing - Part II
Dynamic Manifold Warping for view invariant action recognition
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online human gesture recognition from motion data streams
Proceedings of the 21st ACM international conference on Multimedia
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We address the problem of unsupervised online segmenting human motion sequences into different actions. Kernelized Temporal Cut (KTC), is proposed to sequentially cut the structured sequential data into different regimes. KTC extends previous works on online change-point detection by incorporating Hilbert space embedding of distributions to handle the nonparametric and high dimensionality issues. Based on KTC, a realtime online algorithm and a hierarchical extension are proposed for detecting both action transitions and cyclic motions at the same time. We evaluate and compare the approach to state-of-the-art methods on motion capture data, depth sensor data and videos. Experimental results demonstrate the effectiveness of our approach, which yields realtime segmentation, and produces higher action segmentation accuracy. Furthermore, by combining with sequence matching algorithms, we can online recognize actions of an arbitrary person from an arbitrary viewpoint, given realtime depth sensor input.