JOURNAL ARTICLE

Person Localization System Using Privacy-Preserving Sensor

Shota NakashimaHui LüKohei MiyataYuhki KitazonoSeiichi Serikawa

Year: 2011 Journal:   Applied Mechanics and Materials Vol: 103 Pages: 622-627   Publisher: Trans Tech Publications

Abstract

A privacy-preserving sensor for person localization has been developed. In theory, the sensor can be constructed with a line sensor and cylindrical lens because only a one-dimensional brightness distribution is needed. However, a line sensor is expensive. In contrast, CMOS area sensors are low cost and are increasing in sensitivity according to recent rapid advancement in the technology. Therefore, we covered the CMOS area sensor physically so that it behaved as a line sensor, we substituted CMOS sensors for the line sensors in practice. The proposed sensor obtains a one-dimensional horizontal brightness distribution that is approximately equal to the integration value of each vertical pixel line of the two-dimensional image. It is impossible to restore the two-dimensional detail texture image from one-dimensional brightness distribution, although it obtains enough information to detect a person’s position and movement status. Thus, the privacy is protected. Moreover, the appearance of the proposed sensor is very different from the conventional video camera, so the psychological resistance of having a picture taken is reduced. In this work, we made the privacy preserving sensor practically, and verified whether a person’s state was able to be detected. The simulation results show that the proposed sensor can detect a present person’s state responsively without violating privacy.

Keywords:
Brightness Image sensor Computer vision Line (geometry) Artificial intelligence Pixel Computer science CMOS sensor Sensitivity (control systems) Real-time computing Engineering Electronic engineering Optics Physics Mathematics

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1
Cited By
0.26
FWCI (Field Weighted Citation Impact)
8
Refs
0.56
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Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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