Landmarks inside the shape: Shape matching using image descriptors

Date

2016-01-01

Author

Guler, R. A.
Tarı, Zehra Sibel
ÜNAL, GÖZDE

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

299
views

0
downloads

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.

Subject Keywords

Object recognıtıon, Diffusion process, Scale, Algorithm, Features

URI

https://hdl.handle.net/11511/32701

Journal

PATTERN RECOGNITION

DOI

https://doi.org/10.1016/j.patcog.2015.07.013

Collections

Department of Computer Engineering, Article

Suggestions

OpenMETU
Core

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...
Multiple linear regression model with stochastic design variables İslam, Muhammed Qamarul (Informa UK Limited, 2010-01-01) In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.
Comparison of generative and discriminative techniques for object detection and classification Ulusoy, İlkay (2004-01-01) 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...
Comparison of Dictionary-Based Image Reconstruction Algorithms for Inverse Problems Dogan, Didem; Öktem, Sevinç Figen (2020-10-07) 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...
Scaling and Self-Similarity of One-Dimensional Suspended Sediment Transport Equations Carr, K.J.; Ercan, Ali; Kavvas, M.L. (2014-01-01) © 2014 American Society of Civil Engineers.The governing physical process of sediment transport can be represented in a scale model without the simplifying assumptions required in numerical modeling, making scale modeling a considerable complement to numerical simulations. However, the current methods utilized in scaling sediment transport in unsteady open-channel flow result in a number of model and scale effects, which decrease the accuracy and applicability of scale models. These model and scale effects ...

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: https://hdl.handle.net/11511/32701.