Region of Interest detection using indoor structure and saliency map

Author

Kataoka, Kotaro ; Sudo, Kyoko ; Morimoto, Masayuki

Author_Institution

NTT Media Intell. Labs., NTT Corp., Yokosuka, Japan

fYear

2012

fDate

11-15 Nov. 2012

Firstpage

3329

Lastpage

3332

Abstract

Detecting and identifying Regions of Interest (ROIs) is an important task for navigation and retrieval services. In this paper, we focus on indoor scene images and detect object regions such as shop signs and merchandise. Our method is based on two approaches; 1) Indoor structure analysis from a single image by learning the types of scenes. 2) Detect ROIs by taking advantage of the relationship of expected locations of planes and objects. We conduct a detection experiment and demonstrate the effectiveness of our proposal.

Keywords

computerised navigation; image retrieval; indoor environment; learning (artificial intelligence); natural scenes; object detection; object recognition; ROI detection; indoor scene images; indoor structure analysis; navigation services; object region detection; region of interest detection; region of interest identification; retrieval services; saliency map; scene learning; Image edge detection; Image segmentation; Merchandise; Navigation; Pattern recognition; Periodic structures; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2012 21st International Conference on

Conference_Location

Tsukuba

ISSN

1051-4651

Print_ISBN

978-1-4673-2216-4

Type

conf

Filename

6460877