Improvement of the Search Ability of S-System (A Function-Discovery System)

Serikawa, Seiichi; Shimomura, Teruo

doi:10.1541/ieejeiss1987.120.8-9_1281

Cited by 8 publications

(5 citation statements)

References 1 publication

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“…The 1-D brightness distribution contained the human state and we used the LVQ (7) as the algorithm for estimating the human state. Furthermore, in order to obtain the optimum parameters of the LVQ, we used the S-System (8)(9) , which is one of the extended models of GA (10) and GP (11) . Thus, a privacy-preserving sensor that differentiates between a person who is upright and one who has fallen was made possible without using cameras and vast equipment.…”

Section: One-dimensional Brightness Distribution Sensormentioning

confidence: 99%

Image Reconstruction method for Human Shape Detection Using One-Dimensional Brightness Distribution Sensor

Nakashima

Haruyama

Kitazono

2013

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013

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In this study, a detection of human shape with privacy-preserving by image reconstruction 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. 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. We can recognize the human shape by change of the one-dimensional distribution. However, it's difficult to grasp it without the technical knowledge of the proposed system for average person from the distribution. For that reason, the image of human shape is reconstructed by two distributions, although it is impossible to restore the two-dimensional detail texture image correctly. 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 reconstructed the image using one-dimensional brightness distribution obtained by the privacy-preserving sensor, and verified whether a person's shape was able to be detected. The simulation results show that the proposed sensor can detect a present person's state responsively without violating privacy.

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Section: One-dimensional Brightness Distribution Sensormentioning

confidence: 99%

Image Reconstruction method for Human Shape Detection Using One-Dimensional Brightness Distribution Sensor

Nakashima

Haruyama

Kitazono

2013

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013

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show abstract

“…The one-dimensional brightness distribution contained the human state and we used the LVQ [6] as the algorithm for estimating the human state. Furthermore, in order to obtain the optimum parameters of the LVQ, we used the S-System [7][8], which is one of the extended models of GA [9] and GP [10]. Thus, a privacy-preserving sensor that differentiates between a person who is upright and one who has fallen was made possible without using cameras and vast equipment.…”

Section: Privacy-preventive Sensormentioning

confidence: 99%

Person Localization System Using Privacy-Preserving Sensor

Nakashima

Miyata

et al. 2011

AMM

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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.

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“…These are referred to as S-Systems because they are systems that use the concept of sexless reproduction [3]. An improved system has since been proposed [4]. However, both GP and S-Systems sometimes cannot generate a good approximation function when the waveform of the observed data is complex.…”

Section: Introductionmentioning

confidence: 99%