American Journal of Systems and Software
ISSN (Print): 2372-708X ISSN (Online): 2372-7071 Website: Editor-in-chief: Josué-Antonio Nescolarde-Selva
Open Access
Journal Browser
American Journal of Systems and Software. 2017, 5(1), 9-14
DOI: 10.12691/ajss-5-1-2
Open AccessArticle

DiFace: A Face-based Video Retrieval System with Distributed Computing

Lan Huang1, and Juan Zhou1

1College of Computer Science, Yangtze University, Jingzhou, Hubei, China

Pub. Date: August 24, 2017

Cite this paper:
Lan Huang and Juan Zhou. DiFace: A Face-based Video Retrieval System with Distributed Computing. American Journal of Systems and Software. 2017; 5(1):9-14. doi: 10.12691/ajss-5-1-2


With the prevalence of video surveillance and the extraordinary number of online video resources, the demand for effective and efficient content-based video analysis tools has shown significant growth in recent years. Human face has always been one of the most important interest points in automatic video analysis. In this paper, we designed a face-based video retrieval system. We analyzed the three key issues in constructing such systems: frame extraction based on face detection, key frame selection based on face tracking and relevant video retrieval using PCA-based face matching. In order to cope with the huge number of videos, we implemented a prototype system on the Hadoop distributed computing framework: DiFace. We populated the system with a baseline dataset consisting of TED talk fragments, provided by the 2014 Chinese national big data contest. Empirical experimental results showed the effectiveness of the system architecture and also the techniques employed.

video retrieval face-based video retrieval content-based retrieval distributed computing Hadoop

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit


[1]  Dey, S., Chakraborty, A., Naskar, S., Misra, P.. Smart city surveillance: Leveraging benefits of cloud data stores. In: IEEE 37th Conference on Local Computer Networks Workshops, 2012, IEEE, pp. 868-876.
[2]  Boyd, D. M., Ellison, N. B.. Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 2007, 13(1), pp. 210-230.
[3]  Satoh, S., Nakamura, Y., Kanade, T.. Name-It: Naming and Detecting Faces in News Videos. Journal of IEEE MultiMedia, 1999, 6(1), pp. 22-35.
[4]  Pande, N., Jain, M., Kapil, D., Guha, P.. The Video Face Book. In: 18th International Conference on Advances in Multimedia Modeling, 2012, IEEE, pp. 495-506.
[5]  Zhang, N., Jeong, H-Y.. A Retrieval Algorithm for Specific Face Images in Airport Surveillance Multimedia Videos on Cloud Computing Platform, 2017, 76(16), pp. 17129-17143.
[6]  Lee, Y-S., Hsu, C-Y., Lin, P-C., Chen, C-Y., Wang, J-C.. Video summarization based on face recognition and speaker verification. In 10th Conference on Industrial Electronics and Applications, 2015, IEEE, pp. 621-625.
[7]  Mandal, B.. Face recognition: Perspectives from the real world. In 14th International Conference on Control, Automation, Robotics and Vision, 2016, IEEE.
[8]  Belaroussi, R., Milgram, M.. A comparative study on face detection and tracking algorithms. Expert Systems with Applications, 2012, 39(8), pp. 7158-7164.
[9]  Zhang, H. J. Wu, J., Zhong, D., Smoliar, S. W.. An integrated system for content-based video retrieval and browsing. Pattern Recognition, 1997, 30(4), pp. 643-658.
[10]  Hu, W., Xie, N., Li, L., Zeng, X., Maybank, S.. A survey on visual content-based video indexing and retrieval. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2011, 41(6), pp. 797-819.
[11]  Lian, S., Nikolaidis, N., Sencar, H. T.. Content-Based Video Copy Detection—A Survey. Intelligent Multimedia Analysis for Security Applications, 2010, pp. 253-273.
[12]  Chikkerur, S., Sundaram, V., Reisslein, M., Karam, L. J.. Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison. IEEE Transactions on Broadcasting, 2011, 57(2), pp. 165-182.
[13]  Popoola, O. P., Wang, K.. Video-Based Abnormal Human Behavior Recognition—A Review. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2012, 42(6), pp. 865-878.
[14]  Zhou, J., Huang, L. A Comparative Study of Local Features in Face-based Video Retrieval. Journal of Computing Science and Engineering, 2017, 11(1), pp. 24-31.
[15]  Yang, H., Shao, L., Zheng, F., Wang, L., Song, Z.. Recent advances and trends in visual tracking: A review. Neurocomputing, 2011, 74(18), pp. 3823-3831.
[16]  Zafeiriou, S., Zhang, C., Zhang, Z.. A survey on face detection in the wild: Past, present and future. Computer Vision and Image Understanding, 2015, 138, pp. 1-24.
[17]  Yu, S-I., Jiang, L., Xu, Z., Yang, Y., Gauptmann, A. G.. Content-Based Video Search over 1 Million Videos with 1 Core in 1 Second. In: 5th ACM International Conference on Multimedia Retrieval, 2015, ACM, pp. 419-426.
[18]  Ryu, C., Lee, D., Jang, M., Kim, C., Seo, E.. Extensible video processing framework in Apache Hadoop. In: 5th IEEE International Conference on Cloud Computing Technology and Science, vol. 2, 2013, IEEE, pp. 305-310.
[19]  Tan, H., Chen, L.. An approach for fast and parallel video processing on Apache Hadoop clusters. In: 2014 IEEE International Conference on Multimedia and Expo, 2014, IEEE, pp. 1-6.
[20]  Viola, P., Jones M. Rapid object detection using a boosted cascade of simple features. In: 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2011, IEEE, pp. 511-518.
[21]  Bhattacharyya, A.. On a measure of divergence between two statistical populations defined by their probability distributions. Bulletin of the Calcutta Mathematical Society, 1943, 35, pp. 99-109.
[22]  Turk, M., Pentland, A.. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 1999, 3(1), 71-86.
[23]  White, T. Hadoop: The Definitive Guide. O'Reilly Media, Inc. 2015.
[24]  MountableHDFS. [Online]. Available: [Accessed: August 17, 2017].
[25]  JavaCV. [Online]. Available: [Accessed: August 17, 2017].