A State-Based Approach to the Representation and Recognition of Gesture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion analysis: a review
Computer Vision and Image Understanding
The String-to-String Correction Problem
Journal of the ACM (JACM)
The Hierarchical Hidden Markov Model: Analysis and Applications
Machine Learning
Multiobject Behavior Recognition by Event Driven Selective Attention Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extraction and Classification of Visual Motion Patterns for Hand Gesture Recognition
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Hidden Markov Model Based Continuous Online Gesture Recognition
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Layered representations for learning and inferring office activity from multiple sensory channels
Computer Vision and Image Understanding - Special issue on event detection in video
Optimising dynamic graphical models for video content analysis
Computer Vision and Image Understanding
Robust Sequential Data Modeling Using an Outlier Tolerant Hidden Markov Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human Action Recognition by Semilatent Topic Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Equivalent key frames selection based on iso-content principles
IEEE Transactions on Circuits and Systems for Video Technology
Human Action Recognition in Videos Using Kinematic Features and Multiple Instance Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multimedia Tools and Applications
Enhanced human behavior recognition using HMM and evaluative rectification
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Robust Human Behavior Modeling from Multiple Cameras
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Action Recognition Using Spatial-Temporal Context
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Future Generation Computer Systems
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
Bayesian filter based behavior recognition in workflows allowing for user feedback
Computer Vision and Image Understanding
Audio–Visual Affective Expression Recognition Through Multistream Fused HMM
IEEE Transactions on Multimedia
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Event detection in field sports video using audio-visual features and a support vector Machine
IEEE Transactions on Circuits and Systems for Video Technology
Event Detection of Broadcast Baseball Videos
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper a framework for automatic online workflow recognition in industrial environments where the issue of concurrent activities rises, is presented. The framework consists of three main parts: The first part is devoted to detecting activity in specific Regions of Interest (ROIs) of the video sequence. This is effected by separating each frame into ROIs and representing the resulting subimages through feature vectors. By observing these vectors we can determine when there is action in a particular ROI. The second part of the framework lies in examining whether the detected activity corresponds to a workflow related event. This is accomplished by HMM modeling. Finally, the third part employs a string matching based technique to confirm the validity of the observed sequence of events or correct any detection or classification errors. This last step also addresses a top down approach by informing lower system levels (such as image representation or object tracking) about the errors committed. The performance of the proposed approach is thoroughly evaluated under real-life complex visual workflow understanding scenarios, in an industrial plant. The obtained results are compared and discussed.