Skip to main content

Nested pictorial structures

Publication ,  Journal Article
Gu, S; Zheng, Y; Tomasi, C
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
October 30, 2012

We propose a theoretical construct coined nested pictorial structure to represent an object by parts that are recursively nested. Three innovative ideas are proposed: First, the nested pictorial structure finds a part configuration that is allowed to be deformed in geometric arrangement, while being confined to be topologically nested. Second, we define nested features which lend themselves to better, more detailed accounting of pixel data cost and describe occlusion in a principled way. Third, we develop the concept of constrained distance transform, a variation of the generalized distance transform, to guarantee the topological nesting relations and to further enforce that parts have no overlap with each other. We show that matching an optimal nested pictorial structure of K parts on an image of N pixels takes O(NK) time using dynamic programming and constrained distance transform. In our MATLAB/C++ implementation, it takes less than 0.1 seconds to do the global optimal matching when K = 10 and N = 400 x 400. We demonstrate the usefulness of nested pictorial structures in the matching of objects of nested patterns, objects in occlusion, and objects that live in a context. © 2012 Springer-Verlag.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

October 30, 2012

Volume

7573 LNCS

Issue

PART 2

Start / End Page

816 / 827

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Gu, S., Zheng, Y., & Tomasi, C. (2012). Nested pictorial structures. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7573 LNCS(PART 2), 816–827. https://doi.org/10.1007/978-3-642-33709-3_58
Gu, S., Y. Zheng, and C. Tomasi. “Nested pictorial structures.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7573 LNCS, no. PART 2 (October 30, 2012): 816–27. https://doi.org/10.1007/978-3-642-33709-3_58.
Gu S, Zheng Y, Tomasi C. Nested pictorial structures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Oct 30;7573 LNCS(PART 2):816–27.
Gu, S., et al. “Nested pictorial structures.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7573 LNCS, no. PART 2, Oct. 2012, pp. 816–27. Scopus, doi:10.1007/978-3-642-33709-3_58.
Gu S, Zheng Y, Tomasi C. Nested pictorial structures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2012 Oct 30;7573 LNCS(PART 2):816–827.

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

Publication Date

October 30, 2012

Volume

7573 LNCS

Issue

PART 2

Start / End Page

816 / 827

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences