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Implementation of a Mobile App for Companion Dog Training using AR and Hand Tracking

AR 및 Hand Tracking을 활용한 반려견 훈련 모바일 앱 구현

  • 최철호 (순천대학교 스마트융합학부) ;
  • 박성욱 (순천대학교 스마트융합학부) ;
  • 정세훈 (순천대학교 인공지능공학부) ;
  • 심춘보 (순천대학교 스마트융합학부)
  • Received : 2023.08.28
  • Accepted : 2023.10.17
  • Published : 2023.10.31

Abstract

With the recent growth of the companion animal market, various social issues related to companion animals have also come to the forefront. Notable problems include incidents of dog bites, the challenge of managing abandoned companion animals, euthanasia, animal abuse, and more. As potential solutions, a variety of training programs such as companion animal-focused broadcasts and educational apps are being offered. However, these options might not be very effective for novice caretakers who are uncertain about what to prioritize in training. While training apps that are relatively easy to access have been widely distributed, apps that allow users to directly engage in training and learn through hands-on experience are still insufficient. In this paper, we propose a more efficient AR-based mobile app for companion animal training, utilizing the Unity engine. The results of usability evaluations indicated increased user engagement due to the inclusion of elements that were previously absent. Moreover, training immersion was enhanced, leading to improved learning outcomes. With further development and subsequent verification and production, we anticipate that this app could become an effective training tool for novice caretakers planning to adopt companion animals, as well as for experienced caretakers.

최근 반려동물 시장 규모가 커짐에 따라 반려동물 관련 사회적 문제도 대두되고 있다. 대표적으로 반려견 물림 사고, 유기견 문제, 안락사, 동물 학대 등이 있다. 대안으로 반려동물 관련 방송, 교육 앱 등 다양한 방식의 훈련 프로그램이 제공되고 있지만, 무엇을 먼저 가르쳐야 할지 모르는 초보 보호자들에게는 그리 효율적이지 못하다. 비교적 접근성이 용이한 훈련 앱이 다수 배포됐지만, 아직 사용자가 직접 훈련을 체험하며 익히는 방식의 앱은 부족한 실정이다. 이에 본 논문에서는 유니티 엔진을 활용해 더욱 효율적인 AR 기반의 반려견 훈련 모바일 앱을 제안한다. 사용성 평가 결과, 기존에 부재했던 요소의 추가로 사용자들 흥미도는 증대했고, 훈련 몰입감까지 제고되어 학습 효과가 향상됐다. 향후 개발 및 양산 검증까지 거쳐 배포된다면 반려동물 입양 계획을 세운 초보 보호자나 기존 보호자들에게 효과적인 훈련 앱이 될 것으로 기대된다.

Keywords

Acknowledgement

본 연구는 문화체육관광부 및 한국콘텐츠진흥원의 2022년도 문화기술 연구개발 사업으로 수행되었음(과제명 : 확장현실 융합 시스템 솔루션 연구개발 기반 문화기술 전문인력 양성, 과제번호 : R2022020014, 기여율 : 100%)

References

  1. M. Ma and W. Tack, "A Study on the Gamification Elements which Applicable to Digital Contents for Dogs," J. of Korea Game Society, vol. 19, no. 3, 2019, pp. 75-86. https://doi.org/10.7583/JKGS.2019.19.3.75
  2. C. Lee, H. Kim, H. Jang and J. Kim, "FRIDOG : Wearable Device for Emotional communication between dogs and dog companions," Korea Computer Congress, vol. 2016, no. 6, 2016, pp. 1455-1457.
  3. J. Lee, Y. Jeong, M. Moon and S. Park, "Development of Dog Name Recommendation System for the Image Abstraction," J. of The Korea Institute of Electronic Communication Sciences, vol. 18, no. 2, 2023, pp. 313-319.
  4. Y. Han, J. Lee, J. Lim, S. Ryu and T. Choi, "Smart Harness for Preventing Pet Loss Outdoors," J. of The Korea Institute of Electronic Communication Sciences, vol. 16, no. 4, 2021, pp. 709-717.
  5. J. Kim, "Review on the problems related with companion animals in Korea," J. Korean Association of Animal Assisted Psychotherapy, vol. 7, no. 1, 2018, pp. 31-37.
  6. Y. Wang and J. Popovic, "Real-time hand-tracking with a color glove," ACM transactions on graphics (TOG), vol. 28, no. 3, 2009, pp. 1-8. https://doi.org/10.1145/1531326.1531369
  7. E. Bylow, J. Sturm, C. Kerl, F. Kahl and D. Cremers, "Real-time camera tracking and 3D reconstruction using signed distance functions," Robotics: Science and Systems, vol. 2, 2013, pp. 2.
  8. H. Kim, "A study on behavior classification enhancement of dogs for human-dog communication," Konkuk University, 2018.
  9. M. Ma and T. Woo, "A Study on the Gamification Elements which Applicable to Digital Contents for Dogs," J. Korea Game Society, vol. 19, no. 3, 2019, pp. 75-86. https://doi.org/10.7583/JKGS.2019.19.3.75