Landmarks inside the shape: Shape matching using image descriptors

Guler, R. A.
Tarı, Zehra Sibel
In the last few decades, significant advances in image matching are provided by rich local descriptors that are defined through physical measurements such as reflectance. As such measurements are not naturally available for silhouettes, existing arsenal of image matching tools cannot be utilized in shape matching. We propose that the recently presented SPEM representation can be used analogous to image intensities to detect local keypoints using invariant image salient point detectors. We devise a shape similarity measure based on the number of matching internal regions. The performance of the similarity measure in planar shape retrieval indicates that the landmarks inside the shape silhouettes provide a strong representation of the regional characteristics of 2D planar shapes.


Multiscale method for feature preserving compression
Tarı, Zehra Sibel (1998-01-01)
Requirements fora good shape representation lead to descriptors that are object centered and that have the notion of scale. These representations usually take the form of shape skeletons at multiple detail levels. Classical tool for skeleton extraction is the grassfire equation, in which the process is lossless and the equation can be run backwards in order to obtain shape boundary from the shape skeleton. Many complicated strategies have been devised to assign significance to skeletal points in order to ar...
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Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the distribution of the image features is modelled. Generative and discriminative methods have very different characteristics, as well as complementary strengths and weaknesses. In this chapter we introduce new generative and discriminative models for object detection and classification based on weakly labelled training data. We use thes...
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Many inverse problems in imaging involve measurements that are in the form of convolutions. Sparsity priors are widely exploited in their solutions for regularization as these problems are generally ill-posed. In this work, we develop image reconstruction methods for these inverse problems using patchbased and convolutional sparse models. The resulting regularized inverse problems are solved via the alternating direction method of multipliers (ADMM). The performance of the developed algorithms is investigat...
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Cycle spinning, a technique mainly used for wavelet denoising, has also been shown to be successful toward image resolution upscaling in the wavelet domain. We propose a directional variant of the cycle spinning methodology. We obtain estimates of local edge orientation from a wavelet decomposition of the available low-resolution image and use this information to influence the choice of cycle spinning parameters that are employed for resolution upscaling. Our experimental results show that the proposed meth...
Citation Formats
R. A. Guler, Z. S. Tarı, and G. ÜNAL, “Landmarks inside the shape: Shape matching using image descriptors,” PATTERN RECOGNITION, pp. 79–88, 2016, Accessed: 00, 2020. [Online]. Available: