Literature DB >> 26353215

Shape Matching Using Multiscale Integral Invariants.

Byung-Woo Hong, Stefano Soatto.   

Abstract

We present a shape descriptor based on integral kernels. Shape is represented in an implicit form and it is characterized by a series of isotropic kernels that provide desirable invariance properties. The shape features are characterized at multiple scales which form a signature that is a compact description of shape over a range of scales. The shape signature is designed to be invariant with respect to group transformations which include translation, rotation, scaling, and reflection. In addition, the integral kernels that characterize local shape geometry enable the shape signature to be robust with respect to undesirable perturbations while retaining discriminative power. Use of our shape signature is demonstrated for shape matching based on a number of synthetic and real examples.

Year:  2015        PMID: 26353215     DOI: 10.1109/TPAMI.2014.2342215

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  4 in total

1.  Enhancing Diffusion MRI Measures By Integrating Grey and White Matter Morphometry With Hyperbolic Wasserstein Distance.

Authors:  Wen Zhang; Jie Shi; Jun Yu; Liang Zhan; Paul M Thompson; Yalin Wang
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2017-06-19

2.  Shape Analysis with Hyperbolic Wasserstein Distance.

Authors:  Jie Shi; Wen Zhang; Yalin Wang
Journal:  Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit       Date:  2016-12-12

3.  Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

Authors:  Zhengyu Su; Wei Zeng; Yalin Wang; Zhong-Lin Lu; Xianfeng Gu
Journal:  Inf Process Med Imaging       Date:  2015

4.  Image Retrieval Using the Fused Perceptual Color Histogram.

Authors:  Guang-Hai Liu; Zhao Wei
Journal:  Comput Intell Neurosci       Date:  2020-11-24
  4 in total

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