An Affine Invariant Region Detector Using the 4th Differential Invariant
ABSTRACT A novel affine invariant region detector based on the 4th differential invariant (DI4) is proposed in this paper. The detector combines scale-space theory with an autocorrelation matrix. Since it is proved that DI4 is a scale- space selection function, feature points and their characteristic scales are first detected by the local maxima of the normalized DI4 over scale-space. Then, the auto-correlation matrices, which are used to describe the affine shapes, are estimated on the characteristic scales of the feature points. The ellipse regions given by the auto-correlation matrices are affine invariant. In order to verify the affine invariance, we build up a simulation experiment to test affine invariance using two single- parameter transforms. The experimental results show the detected regions are invariant to rotation, scale and affine transforms as well as robust to illumination changes.
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ABSTRACT: The paper gives a snapshot of the state of the art in affine covariant region detectors, and compares their performance on a set of test images under varying imaging conditions. Six types of detectors are included: detectors based on affine normalization around Harris (Mikolajczyk and Schmid, 2002; Schaffalitzky and Zisserman, 2002) and Hessian points (Mikolajczyk and Schmid, 2002), a detector of ‘maximally stable extremal regions', proposed by Matas et al.(2002); an edge-based region detector (Tuytelaars and VanGool, 1999) and a detector based on intensity extrema (Tuytelaars and VanGool, 2000), and a detector of ‘salient regions', proposed by Kadir, Zisserman and Brady(2004). The performance is measured against changes in viewpoint, scale, illumination, defocus and image compression. The objective of this paper is also to establish a reference test set of images and performance software, so that future detectors can be evaluated in the same framework.International Journal of Computer Vision 01/2005; 65:43-72. · 3.62 Impact Factor
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ABSTRACT: In this paper, we present a number of enhancements to the Kadir/Brady salient region detector which result in a significant improvement in performance. The modifications we make include: stabilising the difference between consecutive scales when calculating the inter-scale saliency, a new sampling strategy using overlap of pixels, partial volume estimation and parzen windowing. Repeatability is used as the criterion for evaluating the performance of the algorithm. We observe the repeatability for distinctive regions selected from an image and from the same image after applying a particular transformation. The transformations we use include planar rotation, pixel translation, spatial scaling, and intensity shifts and scaling. Experimental results show that the average repeatability rate is improved from 46% to approximately 78% when all the enhancements are applied. We also compare our algorithm with other region detectors on a set of sequences of real images, and our detector outperforms most of the state of the art detectors.Inf. Sci. 01/2007; 177:1088-1122.
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ABSTRACT: The wide-baseline stereo problem, i.e. the problem of establishing correspondences between a pair of images taken from different viewpoints is studied.A new set of image elements that are put into correspondence, the so called extremal regions, is introduced. Extremal regions possess highly desirable properties: the set is closed under (1) continuous (and thus projective) transformation of image coordinates and (2) monotonic transformation of image intensities. An efficient (near linear complexity) and practically fast detection algorithm (near frame rate) is presented for an affinely invariant stable subset of extremal regions, the maximally stable extremal regions (MSER).A new robust similarity measure for establishing tentative correspondences is proposed. The robustness ensures that invariants from multiple measurement regions (regions obtained by invariant constructions from extremal regions), some that are significantly larger (and hence discriminative) than the MSERs, may be used to establish tentative correspondences.The high utility of MSERs, multiple measurement regions and the robust metric is demonstrated in wide-baseline experiments on image pairs from both indoor and outdoor scenes. Significant change of scale (3.5×), illumination conditions, out-of-plane rotation, occlusion, locally anisotropic scale change and 3D translation of the viewpoint are all present in the test problems. Good estimates of epipolar geometry (average distance from corresponding points to the epipolar line below 0.09 of the inter-pixel distance) are obtained.Image and Vision Computing. 01/2004;