Represent, reduce, classify: The essential stages for scene recognition

Author

Ozkan, Savas ; Soysal, Medeni ; Esen, Ersin ; Bozdagi Akar, Gozde

Author_Institution

Goruntu Isleme Grubu, TUBITAK UZAY, Ankara, Turkey

fYear

2015

fDate

16-19 May 2015

Firstpage

1672

Lastpage

1675

Abstract

In this paper, scene recognition problem is investigated in detail by exploiting scene representation, dimension reduction and classification stages. Unlike the other studies, the proposed algorithm has preferred to model the overall structure of the scene instead of an object-based proposal. For that purpose, some of the visual representations like MPEG-7, Gist, BoW, Vlad and Fisher, are classified singly or jointly with Support Vector Machine and Random Forest. The evaluation tests are conducted on MIT indoor dataset [2] and from the results, %31 average precision has been attained by combining Scalable Color, Homogeneous Texture and Vlad with Support Vector Machine.

Keywords

image classification; image colour analysis; image representation; image texture; support vector machines; visual databases; BoW; Fisher; MIT indoor dataset; MPEG-7; SVM; Vlad; classification stages; dimension reduction; homogeneous texture; object-based proposal; random forest; scalable color; scene recognition problem; scene representation; support vector machine; visual representations; Histograms; Kernel; Multimedia communication; Radio frequency; Support vector machines; Transform coding; Visualization; Scene recognition; dimension reduction; supervised classification; visual representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2015 23th

Conference_Location

Malatya

Type

conf

DOI

10.1109/SIU.2015.7130173

Filename

7130173