Due to the limited size of the quiet zone created by active headrests (AHR) near the human ear, noise reduction (NR) at the human ear decreases dramatically when the head moves. Combined with a head tracking system can improve the NR performance when the head moves, but most such studies currently only consider head translation. To improve the robustness when the head translates or rotates, an ear-positioning (EP) system based on a depth camera and human pose estimation model is presented in this paper and integrated with AHR. A post processing method is proposed to address extreme scenarios like an ear being occluded. Experimental results show that the EP system can effectively track the movement of ears. The performance of AHR combined with the system is more robust, achieving the lowest 11.7/12.2 dBA (left ear/right ear) NR for white noise in range of 80-2000 Hz when head translates in a 5 × 5 × 2 grid at a 2.5 cm interval and 11.4/13.6 dBA for head rotation within the range of 60° compared to -5.7/-6.9 and -3.7/2.5 dBA without the system.
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http://dx.doi.org/10.1121/10.0034860 | DOI Listing |
J Acoust Soc Am
January 2025
Key Laboratory of Modern Acoustic, Nanjing University, Nanjing 210093, China.
Due to the limited size of the quiet zone created by active headrests (AHR) near the human ear, noise reduction (NR) at the human ear decreases dramatically when the head moves. Combined with a head tracking system can improve the NR performance when the head moves, but most such studies currently only consider head translation. To improve the robustness when the head translates or rotates, an ear-positioning (EP) system based on a depth camera and human pose estimation model is presented in this paper and integrated with AHR.
View Article and Find Full Text PDFPLoS Biol
September 2016
Department of Psychology and Institute for Systems Research, Program in Neuroscience and Cognitive Science, University of Maryland, College Park, Maryland, United States of America.
Under natural conditions, animals encounter a barrage of sensory information from which they must select and interpret biologically relevant signals. Active sensing can facilitate this process by engaging motor systems in the sampling of sensory information. The echolocating bat serves as an excellent model to investigate the coupling between action and sensing because it adaptively controls both the acoustic signals used to probe the environment and movements to receive echoes at the auditory periphery.
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