N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Human motion analysis: a review
Computer Vision and Image Understanding
The String-to-String Correction Problem
Journal of the ACM (JACM)
An Extension of the String-to-String Correction Problem
Journal of the ACM (JACM)
A technique for computer detection and correction of spelling errors
Communications of the ACM
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
International Journal of Computer Vision
Computation of Normalized Edit Distance and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
International Journal of Computer Vision
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
International Journal of Computer Vision
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Factored conditional restricted Boltzmann Machines for modeling motion style
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Efficient and robust annotation of motion capture data
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Human activity analysis: A review
ACM Computing Surveys (CSUR)
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Berkeley MHAD: A comprehensive Multimodal Human Action Database
WACV '13 Proceedings of the 2013 IEEE Workshop on Applications of Computer Vision (WACV)
Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
| Hi-index | 0.00 |
Much of the existing work on action recognition combines simple features with complex classifiers or models to represent an action. Parameters of such models usually do not have any physical meaning nor do they provide any qualitative insight relating the action to the actual motion of the body or its parts. In this paper, we propose a new representation of human actions called sequence of the most informative joints (SMIJ), which is extremely easy to interpret. At each time instant, we automatically select a few skeletal joints that are deemed to be the most informative for performing the current action based on highly interpretable measures such as the mean or variance of joint angle trajectories. We then represent the action as a sequence of these most informative joints. Experiments on multiple databases show that the SMIJ representation is discriminative for human action recognition and performs better than several state-of-the-art algorithms.