Analogical representation of space and time
Image and Vision Computing
Topology representing networks
Neural Networks
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discovery and Segmentation of Activities in Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-Organizing Maps
Introduction to the Special Section on Video Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Colour Model Selection and Adaption in Dynamic Scenes
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Self-Organizing Network that Can Follow Non-stationary Distributions
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume II
Integration of Image Sequence Evaluation and Fuzzy Metric Temporal Logic Programming
KI '97 Proceedings of the 21st Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
W4: Who? When? Where? What? A Real Time System for Detecting and Tracking People
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Hand Gesture Recognition Following the Dynamics of a Topology-Preserving Network
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Tracking Multiple Objects through Occlusions
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Robust growing neural gas algorithm with application in cluster analysis
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Three-dimensional surface reconstruction using meshing growing neural gas (MGNG)
The Visual Computer: International Journal of Computer Graphics
Machine Vision and Applications
Enhancing change detection in low-quality surveillance footage using markov random fields
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
People tracking and segmentation using spatiotemporal shape constraints
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Video measurement of resident-on-resident physical aggression in nursing homes
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
People detection in image and video data
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Multiple objects tracking in the presence of long-term occlusions
Computer Vision and Image Understanding
Growing neural gas for vision tasks with time restrictions
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Hand gesture recognition via a new self-organized neural network
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
PRISMATICA: toward ambient intelligence in public transport environments
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Tracking multiple nonrigid objects in video sequences
IEEE Transactions on Circuits and Systems for Video Technology
A hierarchical self-organizing approach for learning the patterns of motion trajectories
IEEE Transactions on Neural Networks
`Neural-gas' network for vector quantization and its application to time-series prediction
IEEE Transactions on Neural Networks
A hybrid gradient for n-dimensional images through hyperspherical coordinates
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Growing Self-Organizing Map with cross insert for mixed-type data clustering
Applied Soft Computing
A study of a soft computing based method for 3D scenario reconstruction
Applied Soft Computing
Self-organizing maps with a time-varying structure
ACM Computing Surveys (CSUR)
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The aim of the work is to build self-growing based architectures to support visual surveillance and human-computer interaction systems. The objectives include: identifying and tracking persons or objects in the scene or the interpretation of user gestures for interaction with services, devices and systems implemented in the digital home. The system must address multiple vision tasks of various levels such as segmentation, representation or characterization, analysis and monitoring of the movement to allow the construction of a robust representation of their environment and interpret the elements of the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from acquisition devices at video frequency and offering results to higher level systems, monitors and take decisions in real time, and must accomplish a set of requirements such as: time constraints, high availability, robustness, high processing speed and re-configurability. Based on our previous work with neural models to represent objects, in particular the Growing Neural Gas (GNG) model and the study of the topology preservation as a function of the parameters election, it is proposed to extend the capabilities of this self-growing model to track objects and represent their motion in image sequences under temporal restrictions. These neural models have various interesting features such as: their ability to readjust to new input patterns without restarting the learning process, adaptability to represent deformable objects and even objects that are divided in different parts or the intrinsic resolution of the problem of matching features for the sequence analysis and monitoring of the movement. It is proposed to build an architecture based on the GNG that has been called GNG-Seq to represent and analyze the motion in image sequences. Several experiments are presented that demonstrate the validity of the architecture to solve problems of target tracking, motion analysis or human-computer interaction.