Title
Visual Business Recognition - A Multimodal Approach
Keywords
Business recognition; Business review; Location based service; Map; Multi-hypotheses; Scene text; Storefront; Yelp
Abstract
In this paper we investigate a new problem called visual business recognition. Automatic identification of businesses in images is an interesting task with plenty of potential applications especially for mobile device users. We propose a multimodal approach which incorporates business directories, textual information, and web images in a unified framework. We assume the query image is associated with a coarse location tag and utilize business directories for extracting an over complete list of nearby businesses which may be visible in the image. We use the name of nearby businesses as search keywords in order to automatically collect a set of relevant images from the web and perform image matching between them and the query. Additionally, we employ a text processing method customized for business recognition which is assisted by nearby business names; we fuse the information acquired from image matching and text processing in a probabilistic framework to recognize the businesses. We tested the proposed algorithm on a challenging set of user-uploaded and street view images with promising results for this new application. Copyright © 2013 ACM.
Publication Date
11-18-2013
Publication Title
MM 2013 - Proceedings of the 2013 ACM Multimedia Conference
Number of Pages
665-668
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/2502081.2502174
Copyright Status
Unknown
Socpus ID
84887487128 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84887487128
STARS Citation
Zamir, Amir Roshan; Dehghan, Afshin; and Shah, Mubarak, "Visual Business Recognition - A Multimodal Approach" (2013). Scopus Export 2010-2014. 6479.
https://stars.library.ucf.edu/scopus2010/6479