Learning to track the visual motion of contours
Artificial Intelligence - Special volume on computer vision
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Fast Iris Detection for Personal Verification Using Modular Neural Nets
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
A Rotation Invariant Algorithm for Recognition
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Fast Face Detection Using Neural Networks and Image Decomposition
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
Pedestrian Detection Using Wavelet Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Human iris detection using fast cooperative modular neural nets and image decomposition
Machine Graphics & Vision International Journal
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
Speeding-up normalized neural networks for face/object detection
Machine Graphics & Vision International Journal
New fast normalized neural networks for pattern detection
Image and Vision Computing
EURASIP Journal on Applied Signal Processing
A novel model of neural networks for fast data detection
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
A new approach for fast face detection
NN'06 Proceedings of the 7th WSEAS International Conference on Neural Networks
Fast Code Detection Using High Speed Time Delay Neural Networks
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
A New Implementation for High Speed Normalized Neural Networks in Frequency Space
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part I
A new fast forecasting technique using high speed neural networks
WSEAS Transactions on Signal Processing
A novel fast Kolmogorov's spline complex network for pattern detection
WSEAS TRANSACTIONS on SYSTEMS
A modified Hopfield neural network for perfect calculation of magnetic resonance spectroscopy
WSEAS Transactions on Information Science and Applications
A new technique for detecting dental diseases by using high speed artificial neural networks
WSEAS Transactions on Computers
A real-time intrusion detection algorithm for network security
WSEAS TRANSACTIONS on COMMUNICATIONS
New Fast Decision Tree Classifier for Identifying Protein Coding Regions
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Fast detection of specific information in voice signal over internet protocol
WSEAS TRANSACTIONS on COMMUNICATIONS
Design of anti-GPS for reasons of security
CIS'09 Proceedings of the international conference on Computational and information science 2009
Fast image matching on web pages
WSEAS Transactions on Signal Processing
Fast information retrieval from web pages
WSEAS Transactions on Information Science and Applications
Fast principal component analysis for face detection using cross-correlation and image decomposition
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Fast record detection in large databases using new high speed time delay neural networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A novel high-speed neural model for fast pattern recognition
Soft Computing - A Fusion of Foundations, Methodologies and Applications
New fast principal component analysis for real-time face detection
Machine Graphics & Vision International Journal
Pattern detection using fast normalized neural networks
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Human face detection using new high speed modular neural networks
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
A new expert system for pediatric respiratory diseases by using neural networks
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
A new fast neural network model
ACACOS'12 Proceedings of the 11th WSEAS international conference on Applied Computer and Applied Computational Science
| Hi-index | 0.00 |
In this paper, we present fast neural networks (FNNs) for human motion detection, which might be advantageous especially in various tasks of image tracking. The proposed FNNs uses cross correlation in the frequency domain between the input image and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the FNNs is less than that needed by conventional neural Networks (CNNs). Simulation results using MATLAB confirm the theoretical computations. Then, another neural networks to classify human motion activities (e.g. walking, running) is used. To eliminate the undesirable problems accompanying human motion such as lighting and objects, we adapt and efficiently adapt existing techniques ranging from homomorphic filtering to simple morphological operations. Moreover, an intelligent technique to optimize the process of the moving target, by significantly reducing the number of pixels using the "star" skeletonization is introduced. With this approach, no more than eleven Fourier descriptors are required to completely describe the moving target. The approach is computationally inexpensive and thus ideal for video applications including video surveillance. An experiment to certify this efficiency was performed with 100 % accuracy results.