For Virtual Reality(VR) to be truly immersive, it needs convincing sound to match. Due to the diversity of individual's anthropometric measurements, the individualized customization technology is needed to get con...For Virtual Reality(VR) to be truly immersive, it needs convincing sound to match. Due to the diversity of individual's anthropometric measurements, the individualized customization technology is needed to get convincing sound. In this paper, we proposed a simple and effective method for modeling relationships between anthropometric measurements and Head-related Impulse Response(HRIR). Considering the relationship between anthropometric measurements and different HRIR parts is complicated, we divided the HRIRs into small segments and carried out regression analysis between anthropometric measurements and each segment to establish relationship model. The results of objective simulation and subjective test indicate that the model can generate individualize HRIRs from a series of anthropometric measurements. With the individualized HRIRs, we can get more accurate acoustic localization sense than using non-individualized HRIRs.展开更多
基金supported by the National Key R&D Program of China(No.2017YFB1002803)the National Nature Science Foundation of China(No.61671335,No.U1736206,No.61662010)the Hubei Province Technological Innovation Major Project(No.2016AAA015)
文摘For Virtual Reality(VR) to be truly immersive, it needs convincing sound to match. Due to the diversity of individual's anthropometric measurements, the individualized customization technology is needed to get convincing sound. In this paper, we proposed a simple and effective method for modeling relationships between anthropometric measurements and Head-related Impulse Response(HRIR). Considering the relationship between anthropometric measurements and different HRIR parts is complicated, we divided the HRIRs into small segments and carried out regression analysis between anthropometric measurements and each segment to establish relationship model. The results of objective simulation and subjective test indicate that the model can generate individualize HRIRs from a series of anthropometric measurements. With the individualized HRIRs, we can get more accurate acoustic localization sense than using non-individualized HRIRs.
