University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Feature pairs connected by lines for object recognition

Awais, M and Mikolajczyk, K (2010) Feature pairs connected by lines for object recognition In: 2010 20th ICPR, 2010-08-23 - 2010-08-26, Istanbul, Turkey.

[img] Text
05597286.pdf - ["content_typename_UNSPECIFIED" not defined]
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (1MB)
[img] PDF (licence)
SRI_deposit_agreement.pdf
Restricted to Repository staff only
Available under License : See the attached licence file.

Download (33kB)

Abstract

In this paper we exploit image edges and segmentation maps to build features for object category recognition. We build a parametric line based image approximation to identify the dominant edge structures. Line ends are used as features described by histograms of gradient orientations. We then form descriptors based on connected line ends to incorporate weak topological constraints which improve their discriminative power. Using point pairs connected by an edge assures higher repeatability than a random pair of points or edges. The results are compared with state-of-the-art, and show significant improvement on challenging recognition benchmark Pascal VOC 2007. Kernel based fusion is performed to emphasize the complementary nature of our descriptors with respect to the state-of-the-art features.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
AuthorsEmailORCID
Awais, MUNSPECIFIEDUNSPECIFIED
Mikolajczyk, KUNSPECIFIEDUNSPECIFIED
Date : 2010
Identification Number : https://doi.org/10.1109/ICPR.2010.757
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 13:12
Last Modified : 28 Mar 2017 13:12
URI: http://epubs.surrey.ac.uk/id/eprint/806159

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800