Journal
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 9, Issue 3, Pages 1697-1704Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2013.2245910
Keywords
Building recognition; dimensionality reduction; local oriented features; max pooling; steerable filters
Categories
Funding
- National 863 Program [2013AA013804]
- National Natural Science Foundation of China [61175072, 51165033]
- National Basic Research Program of China [2011CB302400]
- Science and Technology Department of Jiangxi Province of China [20121BBE50023]
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Building recognition is an important task for a wide range of computer vision applications, e. g., surveillance and intelligent navigation aid. However, it is also challenging since each building can be viewed from different angles or under different lighting conditions, for example, resulting in a large variability among building images. A number of building recognition systems have been proposed in recent years. However, most of them are based on a complex feature extraction process. In this paper, we present a new building recognition model based on local oriented features with an arbitrary orientation. Although the newly proposed model is very simple, it offers a modular, computationally efficient, and effective alternative to other building recognition techniques. According to a comparison of experimental results with the state-of-the-art building recognition systems, it is shown that the newly proposed SFBR model can obtain very satisfactory recognition accuracy despite its simplicity.
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