Fig. 1 Configuration of the OpenPose System
Fig. 2 Joint extraction procedure in Open Pose
Fig. 3 k-NN Algorithm (k = 1)
Fig. 4 Decision Tree Algorithm (depth = 9)
Fig. 5 A Child Abuse Judgment System
Fig. 6 Joint Point using OpenPose
Fig. 7 A json file for pose information
Fig. 8 Rear image of an adult and side image of a child
Fig. 9 Child abuse image
Fig. 11 Performance results of the three algorithms for classifying adult and child (AC-Model)
Fig. 12 Performance results of the three algorithms for abuse decision when SVM AC-Model is used
Fig. 10 An ordinary children’s image
Table. 1 Machine Learning Algorithms
Table. 2 Number of Images for training set
Table. 3 Experimental Environment
Table. 4 Performance comparison result of the proposed AC-Model
Table. 5 Performance comparison result of the proposed CA-Model when SVM AC-Model is used
참고문헌
- Central Child Protection Agency, "Child Abuse & Near Korea," 2018.
- B. W. Yoon, "A study on video based child and adult classification with biometry," M.S. thesis, Department of Electrical and Electronic Engineering, University of Kyungsung, Feb. 2015.
- Z. Cao, T. Simon, S. E. Wei, and Y. Sheikh, "Realtime multi-Person 2D Pose Estimation using Part Affinity Fields," in Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7291-7299, 2016.
- S. E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh, "Convolutional Pose Machines," in Proceeding of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4724-4732, 2016.
- S. Qiao, Y. Wang, and J. Li, "Real-time human gesture grading based on OpenPose," in Proceeding of the 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, pp. 1-6, 2017.
- K. S. Ahn, "Comparative Experiment and Evaluation on Machine Learning based k-Nearest Neighbor and Support Vector Machine," M.S. thesis, Department of Information and Communication Engineering, University of Dankook, Dec. 2016.
- T. M. Cover, and P. E. Hart, "Nearest neighbor pattern classification," IEEE Transactions on Information Theory, vol. it-13, no. 1, pp. 21-27, 1967.
- Y. Tang, "Deep learning using linear support vector machines," Workshop on Challenges in Representation Learning, ICML, 2013.
- C. C. Chang, and C. J. Lin, "LIBSVM: A library for support vector machines," Transaction on Intelligent Systems and Technology, vol. 2(3), no. 27, Nov. 2011.
- S. Tong, and D. Koller, "Support Vector Machine Active Learning with Applications to Text Classification," Journal of Machine Learning Research, vol.2(1), pp. 45-66, Nov. 2002.
- A. Papagelis, and D. Kalles, "Breeding Decision Trees Using Evolutionary Techniques," in Proceeding of the Eighteenth International Conference on Machine Learning, pp. 93-400, 2001.
- CMU-Perceptual-Computing-La. OpenPose [Internet]. Available: https://github.com/CMU-Perceptual-Computing-Lab/openpose.
- A. C. Muller and S. Guido, Machine Learning with Python, 1st ed. Germany, O'Reilly Media Inc, 2016.
- Image Set. [Internet]. Available: https://image-net.org/.
피인용 문헌
- 수직 히스토그램 기반 그림자 제거 알고리즘을 이용한 영상 감지 시스템 설계 및 구현 vol.24, pp.1, 2019, https://doi.org/10.6109/jkiice.2020.24.1.91