A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Scatter Search: Methodology and Implementations in C
Scatter Search: Methodology and Implementations in C
Fast Hand Gesture Recognition for Real-Time Teleconferencing Applications
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
A Particle Filter to Track Multiple Objects
WOMOT '01 Proceedings of the IEEE Workshop on Multi-Object Tracking (WOMOT'01)
Scatter search particle filter to solve the dynamic travelling salesman problem
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Multi-dimensional visual tracking using scatter search particle filter
Pattern Recognition Letters
On knowledge modelling of the Visual Tracking task
Expert Systems with Applications: An International Journal
Upper body tracking for human-machine interaction with a moving camera
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A robust particle filter-based face tracker using combination of color and geometric information
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
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This paper presents the scatter search particle filter (SSPF) algorithm and its application to real-time hands and face tracking. SSPF combines sequential Monte Carlo (particle filter) and combinatorial optimization (scatter search) methods. Hands and face are characterized using a skin-color model based on explicit RGB region definition. The hybrid SSPF approach enhances the performance of classical particle filter, reducing the required evaluations of the weighting function and increasing the quality of the estimated solution. The system operates on 320x240 live video in real-time.