Abstract
With the development of computer vision, the traditional identity verifying methods have not been satisfied people’s demand. Also, iris and fingerprint detections rely on devices, so these cannot be used in large scope. Face detection is a fundamental and important research theme in the topic of Pattern Recognition and Computer Vision.This paper proposes use improved AdaBoost algorithm,which is much better than normal AdaBoost.
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References
Wang, L., Tao, J., et al.: G-Hadoop: MapReduce across distributed data centers for data-intensive computing. Future Generation Computer Systems 29(3), 739–750 (2013)
Yen, N., Shih, T., Zhao, L., Jin, Q.: Ranking metrics and search guidance for learning object repository. IEEE Transactions on Learning Technologies 3(3), 250–264 (2010)
Yen, N., Shih, T., Jin, Q.: LONET: an interactive search network for intelligent lecture path generation. ACM Transactions on Intelligent Systems and Technology 4(2), 30 (2013)
Luo, X., Xu, Z., Yu, J., Chen, X.: Building Association Link Network for Semantic Link on Web Resources. IEEE Transactions on Automation Science and Engineering 8(3), 482–494 (2011)
Xu, Z., Luo, X., Wang, L.: Incremental building association link net-work. Computer Systems Science and Engineering 26(3), 153–162 (2011)
Yuan, D., Yang, Y., Liu, X., Li, W., Cui, L., Xu, M., Chen, J.: A highly practical approach towards achieving minimum datasets storage cost in the cloud. IEEE Transactions on Parallel and Distributed Systems 24(6), 1234–1244 (2013)
Zhang, X., Liu, C., Nepal, S., Pandev, S., Chen, J.: A privacy leakage upper-bound constraint based approach for cost-effective privacy preserving of intermediate datasets in cloud. IEEE Transactions on Parallel and Distributed Systems 24(6), 1192–1202 (2013)
Wang, L., Khan, S., et al.: Energy-aware parallel task scheduling in a cluster. Future Generation Computer Systems 29(7), 1661–1670 (2013)
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Zhao, B. (2014). Target Monitoring on Face Detection Based on Improved AdaBoost Algorithm. In: Park, J., Pan, Y., Kim, CS., Yang, Y. (eds) Future Information Technology. Lecture Notes in Electrical Engineering, vol 309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55038-6_57
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DOI: https://doi.org/10.1007/978-3-642-55038-6_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-55037-9
Online ISBN: 978-3-642-55038-6
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