A function estimation approach to sequential learning with neural networks
Neural Computation
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
The scientist and engineer's guide to digital signal processing
The scientist and engineer's guide to digital signal processing
EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation
International Journal of Computer Vision
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color-Based Tracking of Heads and Other Mobile Objects at Video Frame Rates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Real Time Face and Object Tracking as a Component of a Perceptual User Interface
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Sparse Bayesian Learning for Efficient Visual Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast learning in networks of locally-tuned processing units
Neural Computation
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Online updating appearance generative mixture model for meanshift tracking
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Probabilistic object tracking based on machine learning and importance sampling
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Fast and Accurate Online Sequential Learning Algorithm for Feedforward Networks
IEEE Transactions on Neural Networks
Online learning neural tracker
Neurocomputing
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Visual tracking has been a challenging problem in computer vision over the decades. The applications of visual tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. In this paper, we present a novel online adaptive object tracker based on fast learning radial basis function (RBF) networks. Pixel based color features are used for developing the target/object model. Here, two separate RBF networks are used, one of which is trained to maximize the classification accuracy of object pixels, while the other is trained for non-object pixels. The target is modeled using the posterior probability of object and non-object classes. Object localization is achieved by iteratively seeking the mode of the posterior probability of the pixels in each of the subsequent frames. An adaptive learning procedure is presented to update the object model in order to tackle object appearance and illumination changes. The superior performance of the proposed tracker is illustrated with many complex video sequences, as compared against the popular color-based mean-shift tracker. The proposed tracker is suitable for real-time object tracking due to its low computational complexity.