• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.155-156
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• 2014

본 논문에서는 키넥트 기반의 동물농장 게임을 설계하고 구현한다. 이 게임은 다양한 동물과 울음소리를 이용하여 유아의 지능 및 신체 발달을 목적으로 하는 유아 교육용 게임이다. 다양한 동물 이미지는 랜덤하게 화면에 출력되고, 플레이어는 화면에 출력된 동물 이미지를 순서대로 터치함으로써 점수를 획득하도록 구현한다. 또한 화면에 출력된 동물 이미지를 터치하면 해당 동물의 울음소리를 출력하도록 구현한다. 플레이어의 동작은 키넥트를 이용하여 인지한 플레이어의 스켈리톤 정보를 전송 받아 이용한다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.40-49
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• 2009

HAO is a ORB engine to support the logic-based CORBA development environments in FPGA. In this papers, in order to support the logic component developments with HAO, we proposes the translation rule from IDL to VHDL, and the generation of skeleton logic code following the rule. It enables to guarantee the interoperability between the components in distributed multi processor environments includes the general purpose processor and FPGAs, and to improve the performance through the usage of logic-circuit.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.731-736
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• 2008

In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.530-536
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• 2020

The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.