3-D sound for virtual reality and multimedia
3-D sound for virtual reality and multimedia
Drishti: An Integrated Navigation System for Visually Impaired and Disabled
ISWC '01 Proceedings of the 5th IEEE International Symposium on Wearable Computers
Acoustic virtual reality performing man-machine interfacing of the blind
ICS'08 Proceedings of the 12th WSEAS international conference on Systems
Obstacles detection system for visually impaired guidance
ICS'08 Proceedings of the 12th WSEAS international conference on Systems
Generation of the head related transfer functions using artificial neural networks
ICC'09 Proceedings of the 13th WSEAS international conference on Circuits
Biomimetic Sonar System Performing Spectrum-Based Localization
IEEE Transactions on Robotics
The GuideCane-applying mobile robot technologies to assist thevisually impaired
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Work directions and new results in electronic travel aids for blind and visually impaired people
WSEAS TRANSACTIONS on SYSTEMS
Multi-subject head related transfer function generation using artificial neural networks
ICS'10 Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume II
Work directions and new results in electronic travel aids for blind and visually impaired people
ICS'10 Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume I
Proceedings of the 15th WSEAS international conference on Systems
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The new Acoustic Virtual Reality (AVR) concept is often used as a man-machine interface in electronic travel aid (ETA), that help blind and visually impaired individuals to navigate in real outdoor environments. According to this concept, the presence of obstacles in the surrounding environment and the path to the desired target will be signalized to the blind subject by burst of sounds, whose virtual source position suggests the position of the real obstacles and the direction of movement, respectively. The practical implementation of the AVR concept requires the so-called Head Related Transfer Functions (HRTFs) to be known in every point of the 3D space and for each subject. These functions can be determined by using a quite complex procedure, which requires many measurements for each individual. In the present paper, an improved version of the previously proposed [12] artificial neural network (ANN) is presented and used, in order to obtain the HRTFs. The proposed method, valid for only one subject, speeds up the implementation of the AVR concept after the ANN training has been completed. Finally, the experimental setup for testing, some experimental results using the new ANNs, conclusions and further developments are also presented.