DocumentCode :
595436
Title :
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
Link To Document :
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