A framework for recognizing multi-agent action from visual evidence
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Recognition of Visual Activities and Interactions by Stochastic Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Recognizing multitasked activities from video using stochastic context-free grammar
Eighteenth national conference on Artificial intelligence
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Human Action Detection Using PNF Propagation of Temporal Constraints
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
The Journal of Machine Learning Research
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Layered representations for learning and inferring office activity from multiple sensory channels
Computer Vision and Image Understanding - Special issue on event detection in video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
IEEE Transactions on Pattern Analysis and Machine Intelligence
Policy recognition in the abstract hidden Markov model
Journal of Artificial Intelligence Research
Propagation networks for recognition of partially ordered sequential action
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatic workflow monitoring in industrial environments
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A method for online analysis of structured processes using bayesian filters and echo state networks
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Egocentric activity monitoring and recovery
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
On hierarchical modelling of motion for workflow analysis from overhead view
Machine Vision and Applications
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We present a method for real-time monitoring of workflows in a constrained environment. The monitoring system should not only be able to recognise the current step but also provide instructions about the possible next steps in an ongoing workflow. In this paper, we address this issue by using a robust approach (HMM-pLSA) which relies on a Hidden Markov Model (HMM) and generative model such as probabilistic Latent Semantic Analysis (pLSA). The proposed method exploits the dynamics of the qualitative spatial relation between pairs of objects involved in a workflow. The novel view-invariant relational feature is based on distance and its rate of change in 3D space. The multiple pair-wise relational features are represented in a multi-dimensional relational state space using an HMM. The workflow monitoring task is inferred from the relational state space using pLSA on datasets, which consist of workflow activities such as ‘hammering nails' and ‘driving screws'. The proposed approach is evaluated for both ‘off-line' (complete observation) and ‘on-line' (partial observation). The evaluation of the novel approach justifies the robustness of the technique in overcoming issues of noise evolving from object tracking and occlusions.