Combining hierarchical segmentation and shape context based recognition

In this paper, we integrate image segmentation and object recognition into one unified process. The process starts from a seed region produced by the initial segmentation. Then it is evolved through alternating shape context based recognition and smaller scale image segmentation, until an object is...

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Bibliographic Details
Published in2008 8th IEEE International Conference on Computer and Information Technology pp. 839 - 844
Main Authors Fenglei Yang, Yue Lu, Ye Duan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Deformable models
Histograms
Horses
Image segmentation
Object recognition
Pixel
Shape
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Summary:In this paper, we integrate image segmentation and object recognition into one unified process. The process starts from a seed region produced by the initial segmentation. Then it is evolved through alternating shape context based recognition and smaller scale image segmentation, until an object is found. In recognition, the thin plate spline (TPS) transformation is employed to locate the difference between the seed region and the defined model, and guide the subsequent evolution process. Experimental results demonstrate the advantages achieved by the combination of hierarchical segmentation and multi-scale shape contexts based recognition.
ISBN:9781424423576
1424423570
DOI:10.1109/CIT.2008.4594783