DocumentCode
595130
Title
A probabilistic framework for logo detection and localization in natural scene images
Author
Roy, Anirban ; Garain, U.
Author_Institution
Comput. Vision & Pattern Recognition Unit, Indian Stat. Inst., Kolkata, India
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
2051
Lastpage
2054
Abstract
This paper presents a probabilistic approach for logo detection and localization in natural scene images. Two probability distributions are computed, one considering the features extracted from the key points located inside a region and the second refers to shape geometry defined by the key points. The barycentric co-ordinates are considered to define the shape statistics. The performance of the proposed approach has been reported on two publicly available datasets: BelgaLogos and Flickr Logos27. It is shown that statistically significant improvement is achieved over a recently proposed method.
Keywords
feature extraction; geometry; natural scenes; object detection; shape recognition; statistical distributions; BelgaLogos; Flickr Logos27; barycentric co-ordinates; feature extraction; natural scene images; probabilistic logo detection framework; probabilistic logo localization framework; probability distribution; publicly available datasets; shape geometry; shape statistics; statistically significant improvement; Accuracy; Databases; Feature extraction; Geometry; Probabilistic logic; Shape; 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
6460563
Link To Document