Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Visual Activities and Interactions by Stochastic Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video-based event recognition: activity representation and probabilistic recognition methods
Computer Vision and Image Understanding - Special issue on event detection in video
Beyond Tracking: Modelling Activity and Understanding Behaviour
International Journal of Computer Vision
Motion features to enhance scene segmentation in active visual attention
Pattern Recognition Letters
Stereovision depth analysis by two-dimensional motion charge memories
Pattern Recognition Letters
Dynamic visual attention model in image sequences
Image and Vision Computing
Learning and inferring transportation routines
Artificial Intelligence
Conceptual representations between video signals and natural language descriptions
Image and Vision Computing
On scene interpretation with description logics
Image and Vision Computing
Expert Systems with Applications: An International Journal
Road-traffic monitoring by knowledge-driven static and dynamic image analysis
Expert Systems with Applications: An International Journal
Navigational strategies in behaviour modelling
Artificial Intelligence
Understanding dynamic scenes based on human sequence evaluation
Image and Vision Computing
A novel sequence representation for unsupervised analysis of human activities
Artificial Intelligence
Policy recognition in the abstract hidden Markov model
Journal of Artificial Intelligence Research
A flexible sequence alignment approach on pattern mining and matching for human activity recognition
Expert Systems with Applications: An International Journal
Video sequence motion tracking by fuzzification techniques
Applied Soft Computing
Real-time motion detection by lateral inhibition in accumulative computation
Engineering Applications of Artificial Intelligence
Human action recognition using boosted EigenActions
Image and Vision Computing
Advances in view-invariant human motion analysis: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Determining the best suited semantic events for cognitive surveillance
Expert Systems with Applications: An International Journal
Agent-oriented modeling and development of a person-following mobile robot
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Learning semantic scene models from observing activity in visual surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Sensor-driven agenda for intelligent home care of the elderly
Expert Systems with Applications: An International Journal
Fuzzy sets for human fall pattern recognition
MCPR'12 Proceedings of the 4th Mexican conference on Pattern Recognition
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
A survey of video datasets for human action and activity recognition
Computer Vision and Image Understanding
Human action recognition based on skeleton splitting
Expert Systems with Applications: An International Journal
Automatic detection of musicians' ancillary gestures based on video analysis
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
There are a number of solutions to automate the monotonous task of looking at a monitor to find suspicious behaviors in video surveillance scenarios. Detecting strange objects and intruders, or tracking people and objects, is essential for surveillance and safety in crowded environments. The present work deals with the idea of jointly modeling simple and complex behaviors to report local and global human activities in natural scenes. Modeling human activities with state machines is still common in our days and is the approach offered in this paper. We incorporate knowledge about the problem domain into an expected structure of the activity model. Motion-based image features are linked explicitly to a symbolic notion of hierarchical activity through several layers of more abstract activity descriptions. Atomic actions are detected at a low level and fed to hand-crafted grammars to detect activity patterns of interest. Also, we work with shape and trajectory to indicate the events related to moving objects. In order to validate our proposal we have performed several tests with some CAVIAR test cases.