A perceptually motivated morphological strategy for shape retrieval

Authors:
Rong-Xiang Hu
Affiliations:
CAS, Hefei Institute of Intelligent Machines, Hefei, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

Citing 9
Cited 0

Shape Matching and Object Recognition Using Shape Contexts

IEEE Transactions on Pattern Analysis and Machine Intelligence
Using the Inner-Distance for Classification of Articulated Shapes

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Hierarchical Procrustes Matching for Shape Retrieval

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Shape Classification Using the Inner-Distance

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient Earth Mover's Distance Algorithm for Robust Histogram Comparison

IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Context-Sensitive Shape Similarity by Graph Transduction

IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving shape retrieval by spectral matching and meta similarity

IEEE Transactions on Image Processing
Co-transduction for shape retrieval

ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Balancing deformability and discriminability for shape matching

ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a perceptually motivated morphological strategy (PMMS) has been proposed to enhance the retrieval performance of common shape matching methods. We introduce a human perception custom that should be considered in a shape retrieval approach, and the proposed strategy based on the closing operation could simulate this custom properly. On the most widely used MPEG-7 dataset, we apply the proposed PMMS to improve the retrieval results of a popular shape matching method named Inner-Distance Shape Contexts (IDSC), and then we use the Locally Constrained Diffusion Process (LCDP) to further enhance the performance. This combination achieves a retrieval rate of 98.53%, which is the state-of-the-art performance on MPEG-7 dataset.