Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108052
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Conference paper |
Title: | Learning graphs to model visual objects across different depictive styles |
Author: | Wu, Q. Cai, H. Hall, P. |
Citation: | Lecture Notes in Artificial Intelligence, 2014 / Fleet, D., Pajdia, T., Schiele, B., Tuytelaars, T. (ed./s), vol.VII, iss.PART 7, pp.313-328 |
Publisher: | Springer |
Issue Date: | 2014 |
Series/Report no.: | Lecture notes in Computer Science |
ISBN: | 9783319105833 |
ISSN: | 0302-9743 1611-3349 |
Conference Name: | 13th European Conference on Computer Vision (ECCV) (6 Sep 2014 - 12 Sep 2014 : Zurich, Switzerland) |
Editor: | Fleet, D. Pajdia, T. Schiele, B. Tuytelaars, T. |
Statement of Responsibility: | Qi Wu, Hongping Cai, and Peter Hall |
Abstract: | Visual object classification and detection are major problems in contemporary computer vision. State-of-art algorithms allow thousands of visual objects to be learned and recognized, under a wide range of variations including lighting changes, occlusion, point of view and different object instances. Only a small fraction of the literature addresses the problem of variation in depictive styles (photographs, drawings, paintings etc.). This is a challenging gap but the ability to process images of all depictive styles and not just photographs has potential value across many applications. In this paper we model visual classes using a graph with multiple labels on each node; weights on arcs and nodes indicate relative importance (salience) to the object description. Visual class models can be learned from examples from a database that contains photographs, drawings, paintings etc. Experiments show that our representation is able to improve upon Deformable Part Models for detection and Bag of Words models for classification. |
Keywords: | Object Recognition; Deformable Models; Multi-labeled Graph; Graph Matching. |
Rights: | © Springer International Publishing Switzerland 2014 |
DOI: | 10.1007/978-3-319-10584-0_21 |
Published version: | http://dx.doi.org/10.1007/978-3-319-10584-0_21 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
RA_hdl_108052.pdf Restricted Access | Restricted Access | 7.52 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.