• Opto-Electronic Engineering
  • Vol. 47, Issue 1, 190135 (2020)
Sun Rui1、2、*, Kan Junsong1、2, Wu Liuwei1、2, and Wang Peng3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.12086/oee.2020.190135 Cite this Article
    Sun Rui, Kan Junsong, Wu Liuwei, Wang Peng. Rotating invariant face detection via cascaded networks and pyramidal optical flows[J]. Opto-Electronic Engineering, 2020, 47(1): 190135 Copy Citation Text show less
    References

    [1] Viola P, Jones M. Rapid object detection using a boosted cas-cade of simple features[C]//Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001.

    [2] Li B, Yang A M, Yang J. Rotated face detection using Ada-Boost[C]//Proceedings of 2010 2nd International Conference on Information Engineering and Computer Science, 2010: 1–4.

    [3] Froba B, Ernst A. Face detection with the modified census transform[C]//Proceedings of the Sixth IEEE International Con-ference on Automatic Face and Gesture Recognition, 2004: 91–96.

    [4] Jin H L, Liu Q S, Lu H Q, et al. Face detection using improved LBP under Bayesian framework[C]//Proceedings of the Third International Conference on Image and Graphics, 2004: 306–309.

    [5] Farfade S S, Saberian M J, Li L J. Multi-view face detection using deep convolutional neural networks[C]//Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, 2015: 643–650.

    [6] Ranjan R, Patel V M, Chellappa R. A deep pyramid deformable part model for face detection[C]//Proceedings of 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems, 2015.

    [7] Yang S, Luo P, Loy C C, et al. From facial parts responses to face detection: a deep learning approach[C]//Proceedings of 2015 IEEE International Conference on Computer Vision, 2015.

    [8] Bas A, Huber P, Smith W A P, et al. 3D morphable models as spatial transformer networks[C]//Proceedings of 2017 IEEE In-ternational Conference on Computer Vision Workshops, 2017.

    [9] Li X X, Liang R H. A review for face recognition with occlusion: from subspace regression to deep learning[J]. Chinese Journal of Computers, 2018, 41(1): 177–207.

    [10] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal net-works[C]//Proceedings of the 28th International Conference on Neural Information Processing Systems, 2015: 91–99.

    [11] Liu W, Anguelov D, Erhan D, et al. Single shot MultiBox detec-tor[C]//Proceedings of the 14th European Conference on Com-pute Vision (ECCV), 2016: 21–37.

    [12] Redmon J, Divvala S, Girshick R, et al. You only look once: unified, real-time object detection[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016.

    [13] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[C]//Proceedings of the 3rd Inter-national Conference on Learning Representations, 2015.

    [14] Li H X, Lin Z, Shen X H, et al. A convolutional neural network cascade for face detection[C]//Proceedings of 2015 IEEE Con-ference on Computer Vision and Pattern Recognition, 2015: 5325–5334.

    [15] Pan R, Wei H Q. Research on human face detection and rec-ognition based on rotation invariance[J]. Computer Engineering and Design, 2009, 30(8): 1941–1943, 1997.

    [22] Zhang K P, Zhang Z P, Li Z F, et al. Joint face detection and alignment using multitask cascaded convolutional networks[J]. IEEE Signal Processing Letters, 2016, 23(10): 1499–1503.

    [23] Yang S, Luo P, Loy C C, et al. WIDER FACE: a face detection benchmark[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016.

    [24] Liu Z W, Luo P, Wang X G, et al. Deep learning face attributes in the wild[C]//Proceedings of 2015 IEEE International Conference on Computer Vision, 2015: 3730–3738.

    [25] Sun Y, Wang X G, Tang X O. Deep convolutional network cas-cade for facial point detection[C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013: 3476–3483.

    [26] K.stinger M, Wohlhart P, Roth P M, et al. Annotated facial landmarks in the wild: a large-scale, real-world database for fa-cial landmark localization[C]//Proceedings of 2011 IEEE Interna-tional Conference on Computer Vision Workshops, 2011: 2144–2151.

    [27] Jain V, Learned-Miller E G. FDDB: A benchmark for face detec-tion in unconstrained settings[R]. UMass Amherst Technical Report, 2010.

    [28] Cascia M L, Sclaroff S. Fast, reliable head tracking under vary-ing illumination[C]// Proceedings of 1999 IEEE Computer So-ciety Conference on Computer Vision and Pattern Recognition, 1999: 604–610.

    [29] Wang H, Li Z F, Ji X, et al. Face R-CNN[C]//2017 IEEE Confe-rence on Computer Vision and Pattern Recognition, 2017.

    Sun Rui, Kan Junsong, Wu Liuwei, Wang Peng. Rotating invariant face detection via cascaded networks and pyramidal optical flows[J]. Opto-Electronic Engineering, 2020, 47(1): 190135
    Download Citation