Skip to Main content Skip to Navigation
Conference papers

Bags of Spatial Relations and Shapes Features for Structural Object Description

Abstract : We introduce a novel bags-of-features framework based on relative position descriptors, modeling both spatial relations and shape information between the pairwise structural subparts of objects. First, we propose a hierarchical approach for the decomposition of complex objects into structural subparts, as well as their description using the concept of Force Histogram Decomposition (FHD). Then, an original learning methodology is presented, in order to produce discriminative hierarchical spatial features for object classification tasks. The cornerstone is to build an homogeneous vocabulary of shapes and spatial configurations occurring across the objects at different scales of decomposition. An advantage of this learning procedure is its compatibility with traditional bags-of-features frameworks, allowing for hybrid representations of both structural and local features. Classification results obtained on two datasets of images highlight the interest of this approach based on hierarchical spatial relations descriptors to recognize structured objects.
Complete list of metadatas

Cited literature [26 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01496896
Contributor : Michaël Clément <>
Submitted on : Thursday, June 1, 2017 - 1:30:36 PM
Last modification on : Saturday, April 11, 2020 - 1:56:39 AM
Document(s) archivé(s) le : Wednesday, September 6, 2017 - 6:39:23 PM

File

icpr2016.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Michaël Clément, Camille Kurtz, Laurent Wendling. Bags of Spatial Relations and Shapes Features for Structural Object Description. International Conference on Pattern Recognition (ICPR), Dec 2016, Cancún, Mexico. pp.1994-1999, ⟨10.1109/ICPR.2016.7899929⟩. ⟨hal-01496896⟩

Share

Metrics

Record views

284

Files downloads

606