Abstract
Ear detection in the wild with the varying pose, lighting, and complex background is a challenging unsolved problem. In this paper, we study affine invariant ear detection in the wild using only a small number of ear example images and formulate the problem of affine invariant ear detection as a task of locating an affine transformation of an ear model in an image. Ear shapes are represented by line segments, which incorporate structural information of line orientation and line-point association. Then a novel fast line based Hausdorff distance (FLHD) is developed to match two sets of line segments. Compared to existing line segment Hausdorff distance, FLHD is one order of magnitude faster with similar discriminative power. As there are a large number of transformations to consider, an efficient global search using branch-and-bound scheme is presented to locate the ear. This makes our algorithm be able to handle arbitrary 2D affine transformations. Experimental results on real-world images that were acquired in the wild and Point Head Pose database show the effectiveness and robustness of the proposed method.
This work was financially supported by the Natural Science Foundation of China (No. 61662034), the Youth Science Foundation of Education Department of Jiangxi Province (No. 150353) and China Scholarship Council (CSC) Scholarship (No. 201609470005).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pei, S.-C., Liou, L.-G.: Finding the motion, position and orientation of a planar patch in 3D space from scaled-orthographic projection. Pattern Recogn. 27(1), 9–25 (1994)
Sarangi, P.P., Panda, M., Mishra, B.S.P., Dehuri, S.: An automated ear localization technique based on modified hausdorff distance. In: Raman, B., Kumar, S., Roy, P.P., Sen, D. (eds.) Proceedings of International Conference on Computer Vision and Image Processing. AISC, vol. 460, pp. 229–240. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-2107-7_21
Gao, Y., Leung, M.K.H.: Line segment Hausdorff distance on face matching. Pattern Recogn. 35(2), 361–371 (2002)
Burge, M., Burger, W.: Ear biometrics in computer vision. In: Proceedings 15th International Conference on Pattern Recognition, pp. 822–826. IEEE, Barcelona (2000)
Hurley, D.J., Nixon, M.S., Carter, J.N.: Force field feature extraction for ear biometrics. Comput. Vis. Image Understand. 98(3), 491–512 (2005)
Prakash, S., Jayaraman, U., Gupta, P.: Connected component based technique for automatic ear detection. In: 16th International Conference on Image Processing (ICIP), pp. 2741–2744. IEEE, USA (2009)
Pflug, A., Winterstein, A., Busch, C.: Robust localization of ears by feature level fusion and context information. In: International Conference on Biometrics (ICB), pp. 1–8. IEEE, Madrid (2013)
Chidananda, P., Srinivas, P., Manikantan, K., Ramachandran, S.: Entropy-cum-hough-transform-based ear detection using ellipsoid particle swarm optimization. Mach. Vis. Appl. 26(2), 185–203 (2015)
Emeršič, Ž., Gabriel, L.L., Štruc, V., Peer, P.: Pixel-wise ear detection with convolutional encoder-decoder networks. arXiv (2017)
Zhang, Y., Mu, Z.: Ear detection under uncontrolled conditions with multiple scale faster region-based convolutional neural networks. Symmetry 9(4), 53 (2017)
Huttenlocher, D.P., Rucklidge, W.J., Klanderman, G.A.: Comparing images using the Hausdorff distance under translation. IEEE Trans. Pattern Anal. Mach. Intell. 15(9), 654–656 (1993)
Dubuisson, M.-P., Jain, A.K.: A modified Hausdorff distance for object matching. In: International Conference on Pattern Recognition, pp. 566–568. IEEE, Jerusalem (1994)
Liu, M.-Y., Tuzel, O., Veeraraghavan, A., Chellappa, R.: Fast directional chamfer matching. In: Computer Vision and Pattern Recognition (CVPR), pp. 1696–1703, IEEE, San Francisco (2010)
Kovesi, P.D.: MATLAB and octave functions for computer vision and image processing (2008)
Fischer, J., Heun, V.: Space-efficient preprocessing schemes for range minimum queries on static arrays. SIAM J. Comput. 40(2), 465–492 (2011)
Gourier, N., Hall, D., Crowley, J.L.: Estimating face orientation from robust detection of salient facial structures. In: FG Net Workshop on Visual Observation of Deictic Gestures, Cambridge, UK, pp. 17–25 (2004)
Gao, Y., Leung, M.: Face recognition using line edge map. IEEE Trans. Pattern Anal. Mach. Intell. 24(6), 764–779 (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Liu, J., Gao, Y., Li, Y. (2018). Few-Example Affine Invariant Ear Detection in the Wild. In: Bai, X., Hancock, E., Ho, T., Wilson, R., Biggio, B., Robles-Kelly, A. (eds) Structural, Syntactic, and Statistical Pattern Recognition. S+SSPR 2018. Lecture Notes in Computer Science(), vol 11004. Springer, Cham. https://doi.org/10.1007/978-3-319-97785-0_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-97785-0_24
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97784-3
Online ISBN: 978-3-319-97785-0
eBook Packages: Computer ScienceComputer Science (R0)