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Content Provider | IEEE Xplore Digital Library |
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Author | Zhigang Zhu Weihong Li Wolberg, G. |
Copyright Year | 2005 |
Description | Author affiliation: The City University of New York (Zhigang Zhu) |
Abstract | This paper describes a multimodal surveillance system for human signature detection. The system consists of three types of sensors: infrared (IR) cameras, pan/tilt/zoom (PTZ) color cameras and laser Doppler vibrometers (LDVs). The LDV is explored as a new non-contact remote voice detector. We have found that voice energy vibrates most objects and the vibrations can be detected by an LDV. Since signals captured by the LDV are very noisy, we have designed algorithms with Gaussian bandpass filtering and adaptive volume scaling to enhance the LDV voice signals. The enhanced voice signals are intelligible from targets without retro-reflective finishes at short or medium distances (<100m). By using retroreflective tapes, the distance could be as far as 300 meters. However, the manual operation to search and focus the laser beam on a target with both vibration and reflection is very difficult at medium and large distances. Therefore, infrared (IR) imaging for target selection and localization is also discussed. Future work remains in automatic LDV targeting and intelligent refocusing for long range LDV listening. |
Starting Page | 10 |
Ending Page | 10 |
File Size | 386069 |
Page Count | 1 |
File Format | |
ISBN | 0769523722 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2005.478 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-09-21 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Humans Sensor systems multimodal integration Vibrometers audio signal enhancement Surveillance Gaussian noise Detectors Object detection infrared video surveillance Infrared sensors Cameras clandestine listening laser vibrometry Signal design |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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