NDLI: Estimating viewing angles in mobile street view search

Content Provider	IEEE Xplore Digital Library
Author	Deli Pei Rongrong Ji Fuchun Sun Huaping Liu
Copyright Year	2012
Description	Author affiliation: Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China (Deli Pei; Fuchun Sun; Huaping Liu) \|\| Department of Electrical Engineering, Columbia University, New York City, 10027, United States (Rongrong Ji)
Abstract	Recent years have witnessed an exciting progress in mobile visual search with applications to location recognition and streaming augmented reality. Most existing works among them are deployed with reference images coming from street views in urban scene. In such scenario, an interesting yet untouched problem is how to determine the viewing angle of the visual query aside of search, which could benefit multidisciplinary applications such as purifying the visual matching and accelerating the streaming AR. In this paper, we study the viewing angle estimation by exploiting the visual appearance of the query, which might be further improved by incorporating the coarse mobile context such as gyro or compass information. Our main idea is to treat this problem as a scene classification problem, upon which the key design is an optimal visual signature to reveal diversity of different viewing angles. We introduce a novel layout based viewing angle descriptor, which is based on carefully designed spatial division as well as appearance feature like color, texture and gradient. We have validated our approach on our dataset containing 1232 street view images in the urban areas of Manhattan, New York City. We show that our proposed descriptor has outperformed several alternatives in holistic image representations, including GIST, HOG and bag-of-feature with spatial pyramid matching.
Starting Page	441
Ending Page	444
File Size	619353
Page Count	4
File Format	PDF
ISBN	9781467325349
ISSN	15224880
e-ISBN	9781467325332
e-ISBN	9781467325325
DOI	10.1109/ICIP.2012.6466891
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile communication Visualization Cities and towns Estimation Urban areas Feature extraction Roads Viewing Angle Prediction Mobile Visual Search Scene Understanding Image Categorization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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