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dc.contributor.authorLiu, Jianming
dc.contributor.authorGao, Yongsheng
dc.contributor.authorLi, Yue
dc.contributor.editorBai, X
dc.contributor.editorHancock, ER
dc.contributor.editorHo, TK
dc.contributor.editorWilson, RC
dc.contributor.editorBiggio, B
dc.contributor.editorRoblesKelly, A
dc.description.abstractEar 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.
dc.publisherSpringer Nature
dc.relation.ispartofconferencenameJoint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) (S+SSPR 2018)
dc.relation.ispartofconferencetitleLecture Notes in Computer Science
dc.relation.ispartoflocationBeijing, China
dc.relation.ispartofpagefrom10 pages
dc.relation.ispartofpageto10 pages
dc.subject.fieldofresearchInformation and computing sciences
dc.titleFew-example affine invariant ear detection in the wild
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
gro.hasfulltextNo Full Text
gro.griffith.authorGao, Yongsheng

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