Shape recognition with edge-based features

Mikolajczyk, Krystian; Zisserman, Andrew; Schmid, Cordelia

doi:10.5244/c.17.79

Cited by 144 publications

(96 citation statements)

References 25 publications

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“…Our work concentrates on the case in between, following the steps of [25,4,[26][27][28]. 2 More specifically, [29,30] have proposed region descriptors for salient regions detected at or near occluding boundaries. While feature selection is traditionally addressed as a representation issue, different from the final goal of recognition, the two processes are beginning to come together [31][32][33].…”

Section: State Of the Artmentioning

confidence: 99%

Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions

Vedaldi

Soatto

2006

Computer Vision – ECCV 2006

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Abstract. We study the set of domain deformations induced on images of three-dimensional scenes by changes of the vantage point. We parametrize such deformations and derive empirical statistics on the parameters, that show a kurtotic behavior similar to that of natural image and range statistics. Such a behavior would suggest that most deformations are locally smooth, and therefore could be captured by simple parametric maps, such as affine ones. However, we show that deformations induced by singularities and occluding boundaries, although rare, are highly salient, thus warranting the development of dedicated descriptors. We therefore illustrate the development of viewpoint invariant descriptors for singularities, as well as for occluding boundaries. We test their performance on scenes where the current state of the art based on affine-invariant region descriptors fail to establish correspondence, highlighting the features and shortcomings of our approach.

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Section: State Of the Artmentioning

confidence: 99%

Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions

Vedaldi

Soatto

2006

Computer Vision – ECCV 2006

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“…A number of more recent works have used edges for object recognition. (Mikolajczyk et al, 2003) generalized Lowe's SIFT descriptors to edge images, where the position and orientation of edges are used to create local shape descriptors that are orientation and scale invariant (Lowe, 1999). (Carmichael & Hebert, 2004) proposed a method to use a cascade of classifiers of increasing aperture size, trained to recognize local edge configurations, to discriminate between object edges and clutter edges; this method, however, is not invariant to changes in image rotation or scale.…”

Section: Related Workmentioning

confidence: 99%

Recognition of Partially Occluded Elliptical Objects using Symmetry on Contour

Cho¹,

Choi²

2007

Vision Systems: Segmentation and Pattern Recognition

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“…Subsequent processing can include texture histograms, color histograms and discriminant analysis [9,11,24]. Mikolajczyk et al [15] employed the use of edge models to obtain correspondences with similar objects. The advantages and disadvantages of using 3D colour histograms in which bins represent location are investigated by Ankerst et al [1].…”

Section: Introductionmentioning

confidence: 99%

An attention based similarity measure used to identify image clusters

Bamidele¹,

Stentiford²

2005

2nd European Workshop on the Integration of Knowledge, Semantics and Digital Media Technology (EWIMT 2005)

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This paper outlines a new attention based similarity measure and describes an application to the problem of identifying image clusters in a 4 class problem. A diverse set of images was obtained using camera phones in 4 separate locations and classification performance was tested against the true location of the images. The approach promises to have application to the unsupervised extraction of unknown numbers of clusters in larger datasets.

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Shape recognition with edge-based features

Cited by 144 publications

References 25 publications

Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions

Viewpoint Induced Deformation Statistics and the Design of Viewpoint Invariant Features: Singularities and Occlusions

Recognition of Partially Occluded Elliptical Objects using Symmetry on Contour

An attention based similarity measure used to identify image clusters

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