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인공지능 객체인식에 관한 파라미터 측정 연구

A Study On Parameter Measurement for Artificial Intelligence Object Recognition

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초록

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

Abstract

Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

참고문헌 (12)

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  2. 얼굴 및 눈 위치 추적을 통한 3DTV 화면 인터페이스제어에 관한 연구, "한국통신학회", ~ (2018)
  3. Y.Y. Yeh, "Limits of fusion and depth judgment in stereoscopic color displays", Human Factors, 32(1), pp.45~60 (2014)
  4. S. Pastoor, "3-D Displays: A review of current technologies", Displays, 17, pp.7~110 (2016)
  5. J.O. Merrit, "Stereoscopic display applications issues-Part 1: Human factor Issues", IS&T, 2013, ~
  6. S. Shiwa, "Proposal for a 3-D display with accommodative compen sation: 3DDAC", Journal of SID, 4, pp.255~261 (2018)
  7. M. Wöpking, "Viewing comfort with stereoscopic pictures: An experimental study on the subjective effects of disparity magnitude and depth of focus", Journal of the SID, 3(3), pp.101~103 (2014)
  8. W. Blohm, "Stereoscopic image representation with synthetic depth of field", Journal of the SID, 5(3), pp.307~313 (2015)
  9. P.Engeldrum, "Psychometric Scaling" (2014), Imcotek Press
  10. N. Hiruma, "Accommodation response to binocular stereoscopic TV images and their viewing conditions", SMPTE Journal, pp.1137~1144 (2018)
  11. 최종명, "모바일 플랫폼을 이용한 상황-인지 멀티미디어 서비스 시스템 분석", (사)디지털산업정보학회 논문지, 2(3), pp.95~102 (2006), (사)디지털산업정보학회
  12. 정도영, "얼굴 특징 정보를 이용한 향상된 눈동자 추적을 통한 졸음운전 경보 시스템 구현", (사)디지털산업정보학회 논문지, 5(2), pp.167~176 (2009), (사)디지털산업정보학회

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